├── Chapter01 ├── c1_01_pv_function.py └── c1_02_julia_good.jl ├── Chapter02 ├── c3_01.R ├── c3_02_pandas_read_csv.py ├── c3_03_pandas_read_csv.py ├── c3_04_save_RDatat.R ├── c3_05_saveRDS.R ├── c3_06_adult_to_pickle.py ├── c3_07_find_definitions_of_inputs.py ├── c3_08_merge_datasets.R ├── c3_09_R_package_sjlabbeld.R ├── c3_10_R_package_foreign.R ├── c3_11_R_package_dslabs.R ├── c3_12_merge_01.py ├── c3_13_merge_02_stock.py ├── c3_14_cbsodata.py ├── c3_15_cbsodata_list_of_data.py ├── c3_16_missing_code_R.R ├── c3_17_missing_code.py ├── c3_18_missing_code_apropos.R ├── c3_19_missing_code.py ├── c3_20_sort_R.R ├── c3_21_sort_order.R ├── c3_22_sort_by2columns.R ├── c3_23_datadotworld.py ├── c3_24_get_iris.py ├── c3_25_sort_Python.py ├── c3_26_ff3monthly2pickle.py ├── c3_27_datadotworld_1.py ├── c3_28_datadotworld_2good.py ├── c3_29_merge_different_names.py ├── c3_30_merge_left_index.py └── c3_31_merge_by2variables.py ├── Chapter03 ├── c3_01.R ├── c3_02_pandas_read_csv.py ├── c3_03_pandas_read_csv.py ├── c3_04_save_RDatat.R ├── c3_05_saveRDS.R ├── c3_06_adult_to_pickle.py ├── c3_07_find_definitions_of_inputs.py ├── c3_08_merge_datasets.R ├── c3_09_R_package_sjlabbeld.R ├── c3_10_R_package_foreign.R ├── c3_11_R_package_dslabs.R ├── c3_12_merge_01.py ├── c3_13_merge_02_stock.py ├── c3_14_cbsodata.py ├── c3_15_cbsodata_list_of_data.py ├── c3_16_missing_code_R.R ├── c3_17_missing_code.py ├── c3_18_missing_code_apropos.R ├── c3_19_missing_code.py ├── c3_20_sort_R.R ├── c3_21_sort_order.R ├── c3_22_sort_by2columns.R ├── c3_23_datadotworld.py ├── c3_24_get_iris.py ├── c3_25_sort_Python.py ├── c3_26_ff3monthly2pickle.py ├── c3_27_datadotworld_1.py ├── c3_28_datadotworld_2good.py ├── c3_29_merge_different_names.py ├── c3_30_merge_left_index.py ├── c3_31_merge_by2variables.py ├── c3_32_write_sas_write_spss_write_stata.R ├── c3_33_generate_z_csv.R └── c3_34_read_ff3monthly_csv.py ├── Chapter04 ├── c4_01_line.R ├── c4_02_sineFunction.R ├── c4_03_pie.R ├── c4_04_Pyplot_julia.jl ├── c4_05_simpleDraw.py ├── c4_06_add_labels.py ├── c4_07_shaded_area_standard_normal_dist.R ├── c4_08_straghtLine.R ├── c4_09_python_fv.py ├── c4_10_getHistram_IBMreturn.py ├── c4_11_histogram.py ├── c4_12_generate_Black_Scholes_formula.py ├── c4_13_add_trendLine.R ├── c4_14_time_value_of_money.py ├── c4_15_add_Greek_letters.R ├── c4_16_plot_julia.jl ├── c4_17_QuantEcon_julia.jl ├── c4_18.jl ├── c4_19_scatter_plot_PyPlot.jl ├── c4_20_save_pdf.R ├── c4_21_plot_Julia.jl ├── c4_22_brownian_motion_animation.R ├── c4_23_bisection_method.R ├── c4_24_Brownian_motion_html.R ├── c4_25_bisectionMethod_html.R ├── c4_26_qgraph_network.R ├── c4_27_3stock_connection.R ├── c4_28_chi2distribution.R ├── c4_29_annimation_flip_coin.R ├── c4_30_annimation3flip_coin.R ├── c4_31_pie_grey.R ├── c4_32_coin_grey.R └── c4_33_plot_grey.jl ├── Chapter05 ├── c5_01_linear_graph.R ├── c5_02_linear_reg.R ├── c5_03_getIBM_dailyQuandl.py ├── c5_04_get_IBM_monthlyQuandl.py ├── c5_05_get_sp500Daily.py ├── c5_06_get_sp500monthly.py ├── c5_07_random_OLS.py ├── c5_08_remove_missing_data.R ├── c5_09_annual_beta.py ├── c5_10_isna.R ├── c5_11_remove_spna.py ├── c5_12_replace_spna.py ├── c5_13_critival_Tvalue.R ├── c5_14_OLS.jl ├── c5_15_get_IBM_dailyFromQuandl.py ├── c5_16_ibm_beta.py ├── c5_17_ibm_beta.R ├── c5_18_ff3_factor_ibm.R ├── c5_19_critical_Tvalue.py ├── c5_20_ff4_RData.R ├── c5_21_cholesky_01.R ├── c5_22_ff5.R ├── c5_23_number_outliers.R ├── c5_24_critical_value_F_distribution.R ├── c5_25_get_critical_value_F_test.py ├── c5_26_f_ditribution_graph.R ├── c5_27_CAPM.jl ├── c5_28_run_julia_program.jl ├── c5_29_replace_na_with_mean.py ├── c5_30_run_linearRegressionOctave.m ├── c5_31_CAPM.jl ├── ibmMonthly5years.txt └── sp500Monthly5years.txt ├── Chapter06 ├── c6_01_QR_code_for_CNN.R ├── c6_02_rattle.R ├── c6_03_read_csv.R ├── c6_04_titanic02.R ├── c6_05_taskViewFinance.R ├── c6_06_taskView_update.R ├── c6_07_path_rattle_package.R ├── c6_08_install_package.m ├── c6_09_update_package.R ├── c6_10_table6_1.R ├── c6_11_taskView_machineLearning.R ├── c6_12_import_matplotlib.py ├── c6_13_Pkg_add.jl ├── c6_14_remove_update_packages.jl ├── c6_15_load_unload_package.m ├── c6_16_conda_commands.txt ├── c6_17_financialCalculator.R ├── c6_18_source.R ├── c6_19.jl ├── c6_20_myPackage.py ├── c6_21_py_compile.py ├── c6_22_import_myPackage.py ├── c6_23_sys_path.py ├── c6_24_environmentVars.R ├── c6_25_environmentVars.py ├── c6_26_get_environmentVars.m └── c6_27_manual_XLConnect.R ├── Chapter07 ├── c7_01_quatradic_function.R ├── c7_02.R ├── c7_03_convex_function.R ├── c7_04_convex_function2.R ├── c7_05_tangent_line.R ├── c7_06_.R ├── c7_07_optimization_01.py ├── c7_08_optimize_help.py ├── c7_09_help_optimize.py ├── c7_10_3D_graph.R ├── c7_11_ff5industries.R ├── c7_12_load_optim.m ├── c7_13_fminsearch.m ├── c7_14_inline_fmins.m ├── c7_15_fminsearch.m ├── c7_16_optimization_JuPM_Not_working.jl ├── c7_17_optim_example.jl ├── c7_18_efficientFrontier.R ├── c7_19_optimization.m ├── c7_20_JuMP01.jl ├── c7_21_JuMp02.jl ├── c7_22_optim.jl ├── c7_23_lqramsey.py ├── c7_24_lqramsey_with_beta.txt ├── c7_25_lqramsey_with_beta_best.txt ├── c7_26_lqramsey_best.ipynb └── c7_27_lqramsey_best.txt ├── Chapter08 ├── c8_01_dist.R ├── c8_02_cluster.R ├── c8_03_cluster_animals.R ├── c8_04_dendogram_animals.R ├── c8_05_kmeans01.R ├── c8_06_launch_rattle.R ├── c8_07_dir_scipy_cluster.py ├── c8_08_python_hierarchical.py ├── c8_09_randomUniformForest_not_working.R ├── c8_10_wine_quality.R ├── c8_11_randomForest_plot.R ├── c8_12_considerDirection.R ├── c8_13_mixMod_bar.R ├── c8_14_install_taskViewCluster.R ├── c8_15_sklearn.py ├── c8_16_functions_sklearn_cluster.py ├── c8_17_example_cluster.py ├── c8_18_.py ├── c8_19_5points.R ├── c8_20_5pointsCluster.R ├── c8_21_python_hierarchical.py ├── c8_22_load_iris_data.py ├── c8_23_randomNumbersFrom2normal.R ├── c8_24_01.jl ├── c8_25_clustering.jl ├── c8_26_kmean.jl ├── c8_27_package_milk.py ├── c8_28_iris_kMean_sklearn.py ├── c8_29_PCA.py ├── c8_30_plot_ward_structured_vs_unstructured.py ├── c8_31_generate_dendrogram_using20obsWine.R ├── c8_32_6graphs.py ├── c8_33_plot_digits_linkage.ipynb ├── c8_34_plot_digits_linkage.py ├── c8_35_plot_digits_linkage.py ├── c8_36_plot_digits_linkage.ipynb ├── c8_37_other.py ├── c8_38_plot_agglomerative_clustering.ipynb ├── c8_39_plot_agglomerative_clustering.py ├── c8_40_plot_pca_iris.ipynb ├── c8_41_plot_pca_iris.py ├── c8_42_number_of_packages_task_view.txt └── c8_43_webs.txt ├── Chapter09 ├── c9_01_titanic.R ├── c9_02_code_tree_tinatic.R ├── c9_03_simplefied_tree_tinatic.R ├── c9_04_simplist_One_tree_tinatic.R ├── c9_05_NYTime_01.R ├── c9_06_print_iris.py ├── c9_07_Iris.R ├── c9_08_naiveBayes.R ├── c9_09_Bayes_titanic.R ├── c9_10_RTextTools.R ├── c9_11_RTextTool_2.R ├── c9_12_load_iris.py ├── c9_13_short_version.py ├── c9_14_iris_predicted_vs_trueOne.py ├── c9_15_FamaFrench3factorModel.py ├── c9_16_generate_titanicRData.R ├── c9_17_others_1.R ├── c9_18_others_2.R ├── c9_19_logicReg.R ├── c9_20_unique_value_iris.py ├── c9_21_reinforcementLearning.R ├── c9_22_reinforcementLearning_state_same_as_nextState.R ├── c9_23_example.m ├── c9_24_reinforcementLearning_example.R ├── c9_25_octave_good_graph.m ├── c9_26_test.m ├── c9_27_bird.m ├── c9_28_install_Conda.jl ├── c9_29_processing_email.m ├── c9_30_great_test.m ├── c9_31_intall_optiminterp.m ├── c9_32_iris.jl ├── c9_33_bird_Kmeans.m ├── c9_34_Kmean_randomNumbers.jl ├── c9_35_print_algorithms.R ├── c9_36_taskView_machineLearning.R ├── c9_37_list_taskView.txt ├── c9_38_iris_prediction.py ├── c9_39_plot_iris.ipynb ├── c9_40_plot_iris.py ├── c9_41_plot_iris.py ├── c9_42_ff3factorDaily.py ├── c9_44_same_as_c9_14_good.py ├── c9_45_same_as_c9_14_good.py └── c9_input.csv ├── Chapter10 ├── c10_01_using_Liblinear01.R ├── c10_02_using_Liblinear02.R ├── c10_03_help_AppliedPredictiveModeling.R ├── c10_04_data_AppliedPredictiveModeling.R ├── c10_05_simdata.R ├── c10_06_fisher_Z_score.R ├── c10_07_abalone_data_set.txt ├── c10_08_get_UCIdatasets.R ├── c10_09_usGDP.R ├── c10_10_usGDP_graph.R ├── c10_11_seasonality_usGDPquarterly.R ├── c10_12_datarobot_not_working.R ├── c10_13_timeSeries.R ├── c10_14_movingAverage.R ├── c10_15_octave_logistic_gd.m.txt ├── c10_16_summarize_by_date.txt ├── c10_17_sp500_annual_return_nextYear.R ├── c10_18_annual_ret_sp500.txt ├── c10_19_catwalk_not_complete.py ├── c10_20_grangerTest_IBM_sp500.R ├── c10_21_ffMonthly.py ├── c10_22_businessCycle.R ├── c10_23_logistic_reg.m ├── c10_24_ddd.m ├── c10_25_ltfat.m ├── c10_26_pca.m ├── c10_27_Granger_test01.R ├── c10_28_Granger_test02.R ├── c10_29_catwalk_info.txt ├── c10_30_QuantEcon_simulated.jl ├── c10_30_ltfat_example.m └── c10_31_timeUsed.jl ├── Chapter11 ├── c11_01_qt_consol.py ├── c11_02_myfincal.py └── c11_03_dir_fincal.py ├── Chapter12 ├── c12_01_lapply.R ├── c12_02_parallel_01.R ├── c12_03_makeCluster.R ├── c12_04_parallel04.R ├── c12_05_snow_01.R ├── c12_06_plyr_example.R ├── c12_07_snow_parallel_Rmpi_UNIX.R ├── c12_08_pwordfreq.py ├── c12_09_pwordfreq.txt ├── c12_10_plyr_arrange.R ├── c12_11_wordfreq.py ├── c12_12_pi_01.py ├── c12_13_parallel.R ├── c12_14_pi_02.py ├── c12_15_Monte Carlo Options.ipynb ├── c12_16_Monte Carlo Options.ipynb ├── c12_17_taskView.R ├── c12_18_taskview.txt ├── c12_19_parallelpi.py ├── c12_20_parallelpi.txt ├── c12_21_pidigits.py ├── c12_22_pidigits.txt ├── c12_23_pwordfreq.py ├── c12_24_pwordfreq.txt └── c12_25_wordfreq_same_as_c12_11.txt ├── Errata_03_52.png ├── LICENSE ├── README.md └── Software and Hardware list.pdf /Chapter01/c1_01_pv_function.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter01/c1_01_pv_function.py -------------------------------------------------------------------------------- /Chapter01/c1_02_julia_good.jl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter01/c1_02_julia_good.jl -------------------------------------------------------------------------------- /Chapter02/c3_01.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter02/c3_01.R -------------------------------------------------------------------------------- /Chapter02/c3_02_pandas_read_csv.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter02/c3_02_pandas_read_csv.py -------------------------------------------------------------------------------- /Chapter02/c3_03_pandas_read_csv.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter02/c3_03_pandas_read_csv.py -------------------------------------------------------------------------------- /Chapter02/c3_04_save_RDatat.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter02/c3_04_save_RDatat.R -------------------------------------------------------------------------------- /Chapter02/c3_05_saveRDS.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter02/c3_05_saveRDS.R -------------------------------------------------------------------------------- /Chapter02/c3_06_adult_to_pickle.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter02/c3_06_adult_to_pickle.py -------------------------------------------------------------------------------- /Chapter02/c3_07_find_definitions_of_inputs.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter02/c3_07_find_definitions_of_inputs.py -------------------------------------------------------------------------------- /Chapter02/c3_08_merge_datasets.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter02/c3_08_merge_datasets.R -------------------------------------------------------------------------------- /Chapter02/c3_09_R_package_sjlabbeld.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter02/c3_09_R_package_sjlabbeld.R -------------------------------------------------------------------------------- /Chapter02/c3_10_R_package_foreign.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter02/c3_10_R_package_foreign.R -------------------------------------------------------------------------------- /Chapter02/c3_11_R_package_dslabs.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter02/c3_11_R_package_dslabs.R -------------------------------------------------------------------------------- /Chapter02/c3_12_merge_01.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter02/c3_12_merge_01.py -------------------------------------------------------------------------------- /Chapter02/c3_13_merge_02_stock.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter02/c3_13_merge_02_stock.py -------------------------------------------------------------------------------- /Chapter02/c3_14_cbsodata.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter02/c3_14_cbsodata.py -------------------------------------------------------------------------------- /Chapter02/c3_15_cbsodata_list_of_data.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter02/c3_15_cbsodata_list_of_data.py -------------------------------------------------------------------------------- /Chapter02/c3_16_missing_code_R.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter02/c3_16_missing_code_R.R -------------------------------------------------------------------------------- /Chapter02/c3_17_missing_code.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter02/c3_17_missing_code.py -------------------------------------------------------------------------------- /Chapter02/c3_18_missing_code_apropos.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter02/c3_18_missing_code_apropos.R -------------------------------------------------------------------------------- /Chapter02/c3_19_missing_code.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter02/c3_19_missing_code.py -------------------------------------------------------------------------------- /Chapter02/c3_20_sort_R.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter02/c3_20_sort_R.R -------------------------------------------------------------------------------- /Chapter02/c3_21_sort_order.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter02/c3_21_sort_order.R -------------------------------------------------------------------------------- /Chapter02/c3_22_sort_by2columns.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter02/c3_22_sort_by2columns.R -------------------------------------------------------------------------------- /Chapter02/c3_23_datadotworld.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter02/c3_23_datadotworld.py -------------------------------------------------------------------------------- /Chapter02/c3_24_get_iris.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter02/c3_24_get_iris.py -------------------------------------------------------------------------------- /Chapter02/c3_25_sort_Python.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter02/c3_25_sort_Python.py -------------------------------------------------------------------------------- /Chapter02/c3_26_ff3monthly2pickle.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter02/c3_26_ff3monthly2pickle.py -------------------------------------------------------------------------------- /Chapter02/c3_27_datadotworld_1.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter02/c3_27_datadotworld_1.py -------------------------------------------------------------------------------- /Chapter02/c3_28_datadotworld_2good.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter02/c3_28_datadotworld_2good.py -------------------------------------------------------------------------------- /Chapter02/c3_29_merge_different_names.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter02/c3_29_merge_different_names.py -------------------------------------------------------------------------------- /Chapter02/c3_30_merge_left_index.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter02/c3_30_merge_left_index.py -------------------------------------------------------------------------------- /Chapter02/c3_31_merge_by2variables.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter02/c3_31_merge_by2variables.py -------------------------------------------------------------------------------- /Chapter03/c3_01.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter03/c3_01.R -------------------------------------------------------------------------------- /Chapter03/c3_02_pandas_read_csv.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter03/c3_02_pandas_read_csv.py -------------------------------------------------------------------------------- /Chapter03/c3_03_pandas_read_csv.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter03/c3_03_pandas_read_csv.py -------------------------------------------------------------------------------- /Chapter03/c3_04_save_RDatat.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter03/c3_04_save_RDatat.R -------------------------------------------------------------------------------- /Chapter03/c3_05_saveRDS.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter03/c3_05_saveRDS.R -------------------------------------------------------------------------------- /Chapter03/c3_06_adult_to_pickle.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter03/c3_06_adult_to_pickle.py -------------------------------------------------------------------------------- /Chapter03/c3_07_find_definitions_of_inputs.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter03/c3_07_find_definitions_of_inputs.py -------------------------------------------------------------------------------- /Chapter03/c3_08_merge_datasets.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter03/c3_08_merge_datasets.R -------------------------------------------------------------------------------- /Chapter03/c3_09_R_package_sjlabbeld.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter03/c3_09_R_package_sjlabbeld.R -------------------------------------------------------------------------------- /Chapter03/c3_10_R_package_foreign.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter03/c3_10_R_package_foreign.R -------------------------------------------------------------------------------- /Chapter03/c3_11_R_package_dslabs.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter03/c3_11_R_package_dslabs.R -------------------------------------------------------------------------------- /Chapter03/c3_12_merge_01.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter03/c3_12_merge_01.py -------------------------------------------------------------------------------- /Chapter03/c3_13_merge_02_stock.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter03/c3_13_merge_02_stock.py -------------------------------------------------------------------------------- /Chapter03/c3_14_cbsodata.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter03/c3_14_cbsodata.py -------------------------------------------------------------------------------- /Chapter03/c3_15_cbsodata_list_of_data.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter03/c3_15_cbsodata_list_of_data.py -------------------------------------------------------------------------------- /Chapter03/c3_16_missing_code_R.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter03/c3_16_missing_code_R.R -------------------------------------------------------------------------------- /Chapter03/c3_17_missing_code.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter03/c3_17_missing_code.py -------------------------------------------------------------------------------- /Chapter03/c3_18_missing_code_apropos.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter03/c3_18_missing_code_apropos.R -------------------------------------------------------------------------------- /Chapter03/c3_19_missing_code.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter03/c3_19_missing_code.py -------------------------------------------------------------------------------- /Chapter03/c3_20_sort_R.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter03/c3_20_sort_R.R -------------------------------------------------------------------------------- /Chapter03/c3_21_sort_order.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter03/c3_21_sort_order.R -------------------------------------------------------------------------------- /Chapter03/c3_22_sort_by2columns.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter03/c3_22_sort_by2columns.R -------------------------------------------------------------------------------- /Chapter03/c3_23_datadotworld.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter03/c3_23_datadotworld.py -------------------------------------------------------------------------------- /Chapter03/c3_24_get_iris.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter03/c3_24_get_iris.py -------------------------------------------------------------------------------- /Chapter03/c3_25_sort_Python.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter03/c3_25_sort_Python.py -------------------------------------------------------------------------------- /Chapter03/c3_26_ff3monthly2pickle.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter03/c3_26_ff3monthly2pickle.py -------------------------------------------------------------------------------- /Chapter03/c3_27_datadotworld_1.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter03/c3_27_datadotworld_1.py -------------------------------------------------------------------------------- /Chapter03/c3_28_datadotworld_2good.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter03/c3_28_datadotworld_2good.py -------------------------------------------------------------------------------- /Chapter03/c3_29_merge_different_names.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter03/c3_29_merge_different_names.py -------------------------------------------------------------------------------- /Chapter03/c3_30_merge_left_index.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter03/c3_30_merge_left_index.py -------------------------------------------------------------------------------- /Chapter03/c3_31_merge_by2variables.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter03/c3_31_merge_by2variables.py -------------------------------------------------------------------------------- /Chapter03/c3_32_write_sas_write_spss_write_stata.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter03/c3_32_write_sas_write_spss_write_stata.R -------------------------------------------------------------------------------- /Chapter03/c3_33_generate_z_csv.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter03/c3_33_generate_z_csv.R -------------------------------------------------------------------------------- /Chapter03/c3_34_read_ff3monthly_csv.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter03/c3_34_read_ff3monthly_csv.py -------------------------------------------------------------------------------- /Chapter04/c4_01_line.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter04/c4_01_line.R -------------------------------------------------------------------------------- /Chapter04/c4_02_sineFunction.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter04/c4_02_sineFunction.R -------------------------------------------------------------------------------- /Chapter04/c4_03_pie.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter04/c4_03_pie.R -------------------------------------------------------------------------------- /Chapter04/c4_04_Pyplot_julia.jl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter04/c4_04_Pyplot_julia.jl -------------------------------------------------------------------------------- /Chapter04/c4_05_simpleDraw.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter04/c4_05_simpleDraw.py -------------------------------------------------------------------------------- /Chapter04/c4_06_add_labels.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter04/c4_06_add_labels.py -------------------------------------------------------------------------------- /Chapter04/c4_07_shaded_area_standard_normal_dist.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter04/c4_07_shaded_area_standard_normal_dist.R -------------------------------------------------------------------------------- /Chapter04/c4_08_straghtLine.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter04/c4_08_straghtLine.R -------------------------------------------------------------------------------- /Chapter04/c4_09_python_fv.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter04/c4_09_python_fv.py -------------------------------------------------------------------------------- /Chapter04/c4_10_getHistram_IBMreturn.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter04/c4_10_getHistram_IBMreturn.py -------------------------------------------------------------------------------- /Chapter04/c4_11_histogram.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter04/c4_11_histogram.py -------------------------------------------------------------------------------- /Chapter04/c4_12_generate_Black_Scholes_formula.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter04/c4_12_generate_Black_Scholes_formula.py -------------------------------------------------------------------------------- /Chapter04/c4_13_add_trendLine.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter04/c4_13_add_trendLine.R -------------------------------------------------------------------------------- /Chapter04/c4_14_time_value_of_money.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter04/c4_14_time_value_of_money.py -------------------------------------------------------------------------------- /Chapter04/c4_15_add_Greek_letters.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter04/c4_15_add_Greek_letters.R -------------------------------------------------------------------------------- /Chapter04/c4_16_plot_julia.jl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter04/c4_16_plot_julia.jl -------------------------------------------------------------------------------- /Chapter04/c4_17_QuantEcon_julia.jl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter04/c4_17_QuantEcon_julia.jl -------------------------------------------------------------------------------- /Chapter04/c4_18.jl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter04/c4_18.jl -------------------------------------------------------------------------------- /Chapter04/c4_19_scatter_plot_PyPlot.jl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter04/c4_19_scatter_plot_PyPlot.jl -------------------------------------------------------------------------------- /Chapter04/c4_20_save_pdf.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter04/c4_20_save_pdf.R -------------------------------------------------------------------------------- /Chapter04/c4_21_plot_Julia.jl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter04/c4_21_plot_Julia.jl -------------------------------------------------------------------------------- /Chapter04/c4_22_brownian_motion_animation.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter04/c4_22_brownian_motion_animation.R -------------------------------------------------------------------------------- /Chapter04/c4_23_bisection_method.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter04/c4_23_bisection_method.R -------------------------------------------------------------------------------- /Chapter04/c4_24_Brownian_motion_html.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter04/c4_24_Brownian_motion_html.R -------------------------------------------------------------------------------- /Chapter04/c4_25_bisectionMethod_html.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter04/c4_25_bisectionMethod_html.R -------------------------------------------------------------------------------- /Chapter04/c4_26_qgraph_network.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter04/c4_26_qgraph_network.R -------------------------------------------------------------------------------- /Chapter04/c4_27_3stock_connection.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter04/c4_27_3stock_connection.R -------------------------------------------------------------------------------- /Chapter04/c4_28_chi2distribution.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter04/c4_28_chi2distribution.R -------------------------------------------------------------------------------- /Chapter04/c4_29_annimation_flip_coin.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter04/c4_29_annimation_flip_coin.R -------------------------------------------------------------------------------- /Chapter04/c4_30_annimation3flip_coin.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter04/c4_30_annimation3flip_coin.R -------------------------------------------------------------------------------- /Chapter04/c4_31_pie_grey.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter04/c4_31_pie_grey.R -------------------------------------------------------------------------------- /Chapter04/c4_32_coin_grey.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter04/c4_32_coin_grey.R -------------------------------------------------------------------------------- /Chapter04/c4_33_plot_grey.jl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter04/c4_33_plot_grey.jl -------------------------------------------------------------------------------- /Chapter05/c5_01_linear_graph.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter05/c5_01_linear_graph.R -------------------------------------------------------------------------------- /Chapter05/c5_02_linear_reg.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter05/c5_02_linear_reg.R -------------------------------------------------------------------------------- /Chapter05/c5_03_getIBM_dailyQuandl.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter05/c5_03_getIBM_dailyQuandl.py -------------------------------------------------------------------------------- /Chapter05/c5_04_get_IBM_monthlyQuandl.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter05/c5_04_get_IBM_monthlyQuandl.py -------------------------------------------------------------------------------- /Chapter05/c5_05_get_sp500Daily.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter05/c5_05_get_sp500Daily.py -------------------------------------------------------------------------------- /Chapter05/c5_06_get_sp500monthly.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter05/c5_06_get_sp500monthly.py -------------------------------------------------------------------------------- /Chapter05/c5_07_random_OLS.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter05/c5_07_random_OLS.py -------------------------------------------------------------------------------- /Chapter05/c5_08_remove_missing_data.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter05/c5_08_remove_missing_data.R -------------------------------------------------------------------------------- /Chapter05/c5_09_annual_beta.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter05/c5_09_annual_beta.py -------------------------------------------------------------------------------- /Chapter05/c5_10_isna.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter05/c5_10_isna.R -------------------------------------------------------------------------------- /Chapter05/c5_11_remove_spna.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter05/c5_11_remove_spna.py -------------------------------------------------------------------------------- /Chapter05/c5_12_replace_spna.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter05/c5_12_replace_spna.py -------------------------------------------------------------------------------- /Chapter05/c5_13_critival_Tvalue.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter05/c5_13_critival_Tvalue.R -------------------------------------------------------------------------------- /Chapter05/c5_14_OLS.jl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter05/c5_14_OLS.jl -------------------------------------------------------------------------------- /Chapter05/c5_15_get_IBM_dailyFromQuandl.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter05/c5_15_get_IBM_dailyFromQuandl.py -------------------------------------------------------------------------------- /Chapter05/c5_16_ibm_beta.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter05/c5_16_ibm_beta.py -------------------------------------------------------------------------------- /Chapter05/c5_17_ibm_beta.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter05/c5_17_ibm_beta.R -------------------------------------------------------------------------------- /Chapter05/c5_18_ff3_factor_ibm.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter05/c5_18_ff3_factor_ibm.R -------------------------------------------------------------------------------- /Chapter05/c5_19_critical_Tvalue.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter05/c5_19_critical_Tvalue.py -------------------------------------------------------------------------------- /Chapter05/c5_20_ff4_RData.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter05/c5_20_ff4_RData.R -------------------------------------------------------------------------------- /Chapter05/c5_21_cholesky_01.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter05/c5_21_cholesky_01.R -------------------------------------------------------------------------------- /Chapter05/c5_22_ff5.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter05/c5_22_ff5.R -------------------------------------------------------------------------------- /Chapter05/c5_23_number_outliers.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter05/c5_23_number_outliers.R -------------------------------------------------------------------------------- /Chapter05/c5_24_critical_value_F_distribution.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter05/c5_24_critical_value_F_distribution.R -------------------------------------------------------------------------------- /Chapter05/c5_25_get_critical_value_F_test.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter05/c5_25_get_critical_value_F_test.py -------------------------------------------------------------------------------- /Chapter05/c5_26_f_ditribution_graph.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter05/c5_26_f_ditribution_graph.R -------------------------------------------------------------------------------- /Chapter05/c5_27_CAPM.jl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter05/c5_27_CAPM.jl -------------------------------------------------------------------------------- /Chapter05/c5_28_run_julia_program.jl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter05/c5_28_run_julia_program.jl -------------------------------------------------------------------------------- /Chapter05/c5_29_replace_na_with_mean.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter05/c5_29_replace_na_with_mean.py -------------------------------------------------------------------------------- /Chapter05/c5_30_run_linearRegressionOctave.m: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter05/c5_30_run_linearRegressionOctave.m -------------------------------------------------------------------------------- /Chapter05/c5_31_CAPM.jl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter05/c5_31_CAPM.jl -------------------------------------------------------------------------------- /Chapter05/ibmMonthly5years.txt: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter05/ibmMonthly5years.txt -------------------------------------------------------------------------------- /Chapter05/sp500Monthly5years.txt: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter05/sp500Monthly5years.txt -------------------------------------------------------------------------------- /Chapter06/c6_01_QR_code_for_CNN.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter06/c6_01_QR_code_for_CNN.R -------------------------------------------------------------------------------- /Chapter06/c6_02_rattle.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter06/c6_02_rattle.R -------------------------------------------------------------------------------- /Chapter06/c6_03_read_csv.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter06/c6_03_read_csv.R -------------------------------------------------------------------------------- /Chapter06/c6_04_titanic02.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter06/c6_04_titanic02.R -------------------------------------------------------------------------------- /Chapter06/c6_05_taskViewFinance.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter06/c6_05_taskViewFinance.R -------------------------------------------------------------------------------- /Chapter06/c6_06_taskView_update.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter06/c6_06_taskView_update.R -------------------------------------------------------------------------------- /Chapter06/c6_07_path_rattle_package.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter06/c6_07_path_rattle_package.R -------------------------------------------------------------------------------- /Chapter06/c6_08_install_package.m: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter06/c6_08_install_package.m -------------------------------------------------------------------------------- /Chapter06/c6_09_update_package.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter06/c6_09_update_package.R -------------------------------------------------------------------------------- /Chapter06/c6_10_table6_1.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter06/c6_10_table6_1.R -------------------------------------------------------------------------------- /Chapter06/c6_11_taskView_machineLearning.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter06/c6_11_taskView_machineLearning.R -------------------------------------------------------------------------------- /Chapter06/c6_12_import_matplotlib.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter06/c6_12_import_matplotlib.py -------------------------------------------------------------------------------- /Chapter06/c6_13_Pkg_add.jl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter06/c6_13_Pkg_add.jl -------------------------------------------------------------------------------- /Chapter06/c6_14_remove_update_packages.jl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter06/c6_14_remove_update_packages.jl -------------------------------------------------------------------------------- /Chapter06/c6_15_load_unload_package.m: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter06/c6_15_load_unload_package.m -------------------------------------------------------------------------------- /Chapter06/c6_16_conda_commands.txt: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter06/c6_16_conda_commands.txt -------------------------------------------------------------------------------- /Chapter06/c6_17_financialCalculator.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter06/c6_17_financialCalculator.R -------------------------------------------------------------------------------- /Chapter06/c6_18_source.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter06/c6_18_source.R -------------------------------------------------------------------------------- /Chapter06/c6_19.jl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter06/c6_19.jl -------------------------------------------------------------------------------- /Chapter06/c6_20_myPackage.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter06/c6_20_myPackage.py -------------------------------------------------------------------------------- /Chapter06/c6_21_py_compile.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter06/c6_21_py_compile.py -------------------------------------------------------------------------------- /Chapter06/c6_22_import_myPackage.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter06/c6_22_import_myPackage.py -------------------------------------------------------------------------------- /Chapter06/c6_23_sys_path.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter06/c6_23_sys_path.py -------------------------------------------------------------------------------- /Chapter06/c6_24_environmentVars.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter06/c6_24_environmentVars.R -------------------------------------------------------------------------------- /Chapter06/c6_25_environmentVars.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter06/c6_25_environmentVars.py -------------------------------------------------------------------------------- /Chapter06/c6_26_get_environmentVars.m: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter06/c6_26_get_environmentVars.m -------------------------------------------------------------------------------- /Chapter06/c6_27_manual_XLConnect.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter06/c6_27_manual_XLConnect.R -------------------------------------------------------------------------------- /Chapter07/c7_01_quatradic_function.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter07/c7_01_quatradic_function.R -------------------------------------------------------------------------------- /Chapter07/c7_02.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter07/c7_02.R -------------------------------------------------------------------------------- /Chapter07/c7_03_convex_function.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter07/c7_03_convex_function.R -------------------------------------------------------------------------------- /Chapter07/c7_04_convex_function2.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter07/c7_04_convex_function2.R -------------------------------------------------------------------------------- /Chapter07/c7_05_tangent_line.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter07/c7_05_tangent_line.R -------------------------------------------------------------------------------- /Chapter07/c7_06_.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter07/c7_06_.R -------------------------------------------------------------------------------- /Chapter07/c7_07_optimization_01.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter07/c7_07_optimization_01.py -------------------------------------------------------------------------------- /Chapter07/c7_08_optimize_help.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter07/c7_08_optimize_help.py -------------------------------------------------------------------------------- /Chapter07/c7_09_help_optimize.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter07/c7_09_help_optimize.py -------------------------------------------------------------------------------- /Chapter07/c7_10_3D_graph.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter07/c7_10_3D_graph.R -------------------------------------------------------------------------------- /Chapter07/c7_11_ff5industries.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter07/c7_11_ff5industries.R -------------------------------------------------------------------------------- /Chapter07/c7_12_load_optim.m: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter07/c7_12_load_optim.m -------------------------------------------------------------------------------- /Chapter07/c7_13_fminsearch.m: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter07/c7_13_fminsearch.m -------------------------------------------------------------------------------- /Chapter07/c7_14_inline_fmins.m: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter07/c7_14_inline_fmins.m -------------------------------------------------------------------------------- /Chapter07/c7_15_fminsearch.m: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter07/c7_15_fminsearch.m -------------------------------------------------------------------------------- /Chapter07/c7_16_optimization_JuPM_Not_working.jl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter07/c7_16_optimization_JuPM_Not_working.jl -------------------------------------------------------------------------------- /Chapter07/c7_17_optim_example.jl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter07/c7_17_optim_example.jl -------------------------------------------------------------------------------- /Chapter07/c7_18_efficientFrontier.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter07/c7_18_efficientFrontier.R -------------------------------------------------------------------------------- /Chapter07/c7_19_optimization.m: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter07/c7_19_optimization.m -------------------------------------------------------------------------------- /Chapter07/c7_20_JuMP01.jl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter07/c7_20_JuMP01.jl -------------------------------------------------------------------------------- /Chapter07/c7_21_JuMp02.jl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter07/c7_21_JuMp02.jl -------------------------------------------------------------------------------- /Chapter07/c7_22_optim.jl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter07/c7_22_optim.jl -------------------------------------------------------------------------------- /Chapter07/c7_23_lqramsey.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter07/c7_23_lqramsey.py -------------------------------------------------------------------------------- /Chapter07/c7_24_lqramsey_with_beta.txt: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter07/c7_24_lqramsey_with_beta.txt -------------------------------------------------------------------------------- /Chapter07/c7_25_lqramsey_with_beta_best.txt: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter07/c7_25_lqramsey_with_beta_best.txt -------------------------------------------------------------------------------- /Chapter07/c7_26_lqramsey_best.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter07/c7_26_lqramsey_best.ipynb -------------------------------------------------------------------------------- /Chapter07/c7_27_lqramsey_best.txt: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter07/c7_27_lqramsey_best.txt -------------------------------------------------------------------------------- /Chapter08/c8_01_dist.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter08/c8_01_dist.R -------------------------------------------------------------------------------- /Chapter08/c8_02_cluster.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter08/c8_02_cluster.R -------------------------------------------------------------------------------- /Chapter08/c8_03_cluster_animals.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter08/c8_03_cluster_animals.R -------------------------------------------------------------------------------- /Chapter08/c8_04_dendogram_animals.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter08/c8_04_dendogram_animals.R -------------------------------------------------------------------------------- /Chapter08/c8_05_kmeans01.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter08/c8_05_kmeans01.R -------------------------------------------------------------------------------- /Chapter08/c8_06_launch_rattle.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter08/c8_06_launch_rattle.R -------------------------------------------------------------------------------- /Chapter08/c8_07_dir_scipy_cluster.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter08/c8_07_dir_scipy_cluster.py -------------------------------------------------------------------------------- /Chapter08/c8_08_python_hierarchical.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter08/c8_08_python_hierarchical.py -------------------------------------------------------------------------------- /Chapter08/c8_09_randomUniformForest_not_working.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter08/c8_09_randomUniformForest_not_working.R -------------------------------------------------------------------------------- /Chapter08/c8_10_wine_quality.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter08/c8_10_wine_quality.R -------------------------------------------------------------------------------- /Chapter08/c8_11_randomForest_plot.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter08/c8_11_randomForest_plot.R -------------------------------------------------------------------------------- /Chapter08/c8_12_considerDirection.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter08/c8_12_considerDirection.R -------------------------------------------------------------------------------- /Chapter08/c8_13_mixMod_bar.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter08/c8_13_mixMod_bar.R -------------------------------------------------------------------------------- /Chapter08/c8_14_install_taskViewCluster.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter08/c8_14_install_taskViewCluster.R -------------------------------------------------------------------------------- /Chapter08/c8_15_sklearn.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter08/c8_15_sklearn.py -------------------------------------------------------------------------------- /Chapter08/c8_16_functions_sklearn_cluster.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter08/c8_16_functions_sklearn_cluster.py -------------------------------------------------------------------------------- /Chapter08/c8_17_example_cluster.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter08/c8_17_example_cluster.py -------------------------------------------------------------------------------- /Chapter08/c8_18_.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter08/c8_18_.py -------------------------------------------------------------------------------- /Chapter08/c8_19_5points.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter08/c8_19_5points.R -------------------------------------------------------------------------------- /Chapter08/c8_20_5pointsCluster.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter08/c8_20_5pointsCluster.R -------------------------------------------------------------------------------- /Chapter08/c8_21_python_hierarchical.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter08/c8_21_python_hierarchical.py -------------------------------------------------------------------------------- /Chapter08/c8_22_load_iris_data.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter08/c8_22_load_iris_data.py -------------------------------------------------------------------------------- /Chapter08/c8_23_randomNumbersFrom2normal.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter08/c8_23_randomNumbersFrom2normal.R -------------------------------------------------------------------------------- /Chapter08/c8_24_01.jl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter08/c8_24_01.jl -------------------------------------------------------------------------------- /Chapter08/c8_25_clustering.jl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter08/c8_25_clustering.jl -------------------------------------------------------------------------------- /Chapter08/c8_26_kmean.jl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter08/c8_26_kmean.jl -------------------------------------------------------------------------------- /Chapter08/c8_27_package_milk.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter08/c8_27_package_milk.py -------------------------------------------------------------------------------- /Chapter08/c8_28_iris_kMean_sklearn.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter08/c8_28_iris_kMean_sklearn.py -------------------------------------------------------------------------------- /Chapter08/c8_29_PCA.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter08/c8_29_PCA.py -------------------------------------------------------------------------------- /Chapter08/c8_30_plot_ward_structured_vs_unstructured.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter08/c8_30_plot_ward_structured_vs_unstructured.py -------------------------------------------------------------------------------- /Chapter08/c8_31_generate_dendrogram_using20obsWine.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter08/c8_31_generate_dendrogram_using20obsWine.R -------------------------------------------------------------------------------- /Chapter08/c8_32_6graphs.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter08/c8_32_6graphs.py -------------------------------------------------------------------------------- /Chapter08/c8_33_plot_digits_linkage.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter08/c8_33_plot_digits_linkage.ipynb -------------------------------------------------------------------------------- /Chapter08/c8_34_plot_digits_linkage.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter08/c8_34_plot_digits_linkage.py -------------------------------------------------------------------------------- /Chapter08/c8_35_plot_digits_linkage.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter08/c8_35_plot_digits_linkage.py -------------------------------------------------------------------------------- /Chapter08/c8_36_plot_digits_linkage.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter08/c8_36_plot_digits_linkage.ipynb -------------------------------------------------------------------------------- /Chapter08/c8_37_other.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter08/c8_37_other.py -------------------------------------------------------------------------------- /Chapter08/c8_38_plot_agglomerative_clustering.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter08/c8_38_plot_agglomerative_clustering.ipynb -------------------------------------------------------------------------------- /Chapter08/c8_39_plot_agglomerative_clustering.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter08/c8_39_plot_agglomerative_clustering.py -------------------------------------------------------------------------------- /Chapter08/c8_40_plot_pca_iris.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter08/c8_40_plot_pca_iris.ipynb -------------------------------------------------------------------------------- /Chapter08/c8_41_plot_pca_iris.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter08/c8_41_plot_pca_iris.py -------------------------------------------------------------------------------- /Chapter08/c8_42_number_of_packages_task_view.txt: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter08/c8_42_number_of_packages_task_view.txt -------------------------------------------------------------------------------- /Chapter08/c8_43_webs.txt: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter08/c8_43_webs.txt -------------------------------------------------------------------------------- /Chapter09/c9_01_titanic.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter09/c9_01_titanic.R -------------------------------------------------------------------------------- /Chapter09/c9_02_code_tree_tinatic.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter09/c9_02_code_tree_tinatic.R -------------------------------------------------------------------------------- /Chapter09/c9_03_simplefied_tree_tinatic.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter09/c9_03_simplefied_tree_tinatic.R -------------------------------------------------------------------------------- /Chapter09/c9_04_simplist_One_tree_tinatic.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter09/c9_04_simplist_One_tree_tinatic.R -------------------------------------------------------------------------------- /Chapter09/c9_05_NYTime_01.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter09/c9_05_NYTime_01.R -------------------------------------------------------------------------------- /Chapter09/c9_06_print_iris.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter09/c9_06_print_iris.py -------------------------------------------------------------------------------- /Chapter09/c9_07_Iris.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter09/c9_07_Iris.R -------------------------------------------------------------------------------- /Chapter09/c9_08_naiveBayes.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter09/c9_08_naiveBayes.R -------------------------------------------------------------------------------- /Chapter09/c9_09_Bayes_titanic.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter09/c9_09_Bayes_titanic.R -------------------------------------------------------------------------------- /Chapter09/c9_10_RTextTools.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter09/c9_10_RTextTools.R -------------------------------------------------------------------------------- /Chapter09/c9_11_RTextTool_2.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter09/c9_11_RTextTool_2.R -------------------------------------------------------------------------------- /Chapter09/c9_12_load_iris.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter09/c9_12_load_iris.py -------------------------------------------------------------------------------- /Chapter09/c9_13_short_version.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter09/c9_13_short_version.py -------------------------------------------------------------------------------- /Chapter09/c9_14_iris_predicted_vs_trueOne.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter09/c9_14_iris_predicted_vs_trueOne.py -------------------------------------------------------------------------------- /Chapter09/c9_15_FamaFrench3factorModel.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter09/c9_15_FamaFrench3factorModel.py -------------------------------------------------------------------------------- /Chapter09/c9_16_generate_titanicRData.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter09/c9_16_generate_titanicRData.R -------------------------------------------------------------------------------- /Chapter09/c9_17_others_1.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter09/c9_17_others_1.R -------------------------------------------------------------------------------- /Chapter09/c9_18_others_2.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter09/c9_18_others_2.R -------------------------------------------------------------------------------- /Chapter09/c9_19_logicReg.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter09/c9_19_logicReg.R -------------------------------------------------------------------------------- /Chapter09/c9_20_unique_value_iris.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter09/c9_20_unique_value_iris.py -------------------------------------------------------------------------------- /Chapter09/c9_21_reinforcementLearning.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter09/c9_21_reinforcementLearning.R -------------------------------------------------------------------------------- /Chapter09/c9_22_reinforcementLearning_state_same_as_nextState.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter09/c9_22_reinforcementLearning_state_same_as_nextState.R -------------------------------------------------------------------------------- /Chapter09/c9_23_example.m: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter09/c9_23_example.m -------------------------------------------------------------------------------- /Chapter09/c9_24_reinforcementLearning_example.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter09/c9_24_reinforcementLearning_example.R -------------------------------------------------------------------------------- /Chapter09/c9_25_octave_good_graph.m: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter09/c9_25_octave_good_graph.m -------------------------------------------------------------------------------- /Chapter09/c9_26_test.m: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter09/c9_26_test.m -------------------------------------------------------------------------------- /Chapter09/c9_27_bird.m: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter09/c9_27_bird.m -------------------------------------------------------------------------------- /Chapter09/c9_28_install_Conda.jl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter09/c9_28_install_Conda.jl -------------------------------------------------------------------------------- /Chapter09/c9_29_processing_email.m: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter09/c9_29_processing_email.m -------------------------------------------------------------------------------- /Chapter09/c9_30_great_test.m: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter09/c9_30_great_test.m -------------------------------------------------------------------------------- /Chapter09/c9_31_intall_optiminterp.m: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter09/c9_31_intall_optiminterp.m -------------------------------------------------------------------------------- /Chapter09/c9_32_iris.jl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter09/c9_32_iris.jl -------------------------------------------------------------------------------- /Chapter09/c9_33_bird_Kmeans.m: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter09/c9_33_bird_Kmeans.m -------------------------------------------------------------------------------- /Chapter09/c9_34_Kmean_randomNumbers.jl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter09/c9_34_Kmean_randomNumbers.jl -------------------------------------------------------------------------------- /Chapter09/c9_35_print_algorithms.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter09/c9_35_print_algorithms.R -------------------------------------------------------------------------------- /Chapter09/c9_36_taskView_machineLearning.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter09/c9_36_taskView_machineLearning.R -------------------------------------------------------------------------------- /Chapter09/c9_37_list_taskView.txt: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter09/c9_37_list_taskView.txt -------------------------------------------------------------------------------- /Chapter09/c9_38_iris_prediction.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter09/c9_38_iris_prediction.py -------------------------------------------------------------------------------- /Chapter09/c9_39_plot_iris.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter09/c9_39_plot_iris.ipynb -------------------------------------------------------------------------------- /Chapter09/c9_40_plot_iris.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter09/c9_40_plot_iris.py -------------------------------------------------------------------------------- /Chapter09/c9_41_plot_iris.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter09/c9_41_plot_iris.py -------------------------------------------------------------------------------- /Chapter09/c9_42_ff3factorDaily.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter09/c9_42_ff3factorDaily.py -------------------------------------------------------------------------------- /Chapter09/c9_44_same_as_c9_14_good.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter09/c9_44_same_as_c9_14_good.py -------------------------------------------------------------------------------- /Chapter09/c9_45_same_as_c9_14_good.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter09/c9_45_same_as_c9_14_good.py -------------------------------------------------------------------------------- /Chapter09/c9_input.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter09/c9_input.csv -------------------------------------------------------------------------------- /Chapter10/c10_01_using_Liblinear01.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter10/c10_01_using_Liblinear01.R -------------------------------------------------------------------------------- /Chapter10/c10_02_using_Liblinear02.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter10/c10_02_using_Liblinear02.R -------------------------------------------------------------------------------- /Chapter10/c10_03_help_AppliedPredictiveModeling.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter10/c10_03_help_AppliedPredictiveModeling.R -------------------------------------------------------------------------------- /Chapter10/c10_04_data_AppliedPredictiveModeling.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter10/c10_04_data_AppliedPredictiveModeling.R -------------------------------------------------------------------------------- /Chapter10/c10_05_simdata.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter10/c10_05_simdata.R -------------------------------------------------------------------------------- /Chapter10/c10_06_fisher_Z_score.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter10/c10_06_fisher_Z_score.R -------------------------------------------------------------------------------- /Chapter10/c10_07_abalone_data_set.txt: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter10/c10_07_abalone_data_set.txt -------------------------------------------------------------------------------- /Chapter10/c10_08_get_UCIdatasets.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter10/c10_08_get_UCIdatasets.R -------------------------------------------------------------------------------- /Chapter10/c10_09_usGDP.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter10/c10_09_usGDP.R -------------------------------------------------------------------------------- /Chapter10/c10_10_usGDP_graph.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter10/c10_10_usGDP_graph.R -------------------------------------------------------------------------------- /Chapter10/c10_11_seasonality_usGDPquarterly.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter10/c10_11_seasonality_usGDPquarterly.R -------------------------------------------------------------------------------- /Chapter10/c10_12_datarobot_not_working.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter10/c10_12_datarobot_not_working.R -------------------------------------------------------------------------------- /Chapter10/c10_13_timeSeries.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter10/c10_13_timeSeries.R -------------------------------------------------------------------------------- /Chapter10/c10_14_movingAverage.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter10/c10_14_movingAverage.R -------------------------------------------------------------------------------- /Chapter10/c10_15_octave_logistic_gd.m.txt: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter10/c10_15_octave_logistic_gd.m.txt -------------------------------------------------------------------------------- /Chapter10/c10_16_summarize_by_date.txt: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter10/c10_16_summarize_by_date.txt -------------------------------------------------------------------------------- /Chapter10/c10_17_sp500_annual_return_nextYear.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter10/c10_17_sp500_annual_return_nextYear.R -------------------------------------------------------------------------------- /Chapter10/c10_18_annual_ret_sp500.txt: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter10/c10_18_annual_ret_sp500.txt -------------------------------------------------------------------------------- /Chapter10/c10_19_catwalk_not_complete.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter10/c10_19_catwalk_not_complete.py -------------------------------------------------------------------------------- /Chapter10/c10_20_grangerTest_IBM_sp500.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter10/c10_20_grangerTest_IBM_sp500.R -------------------------------------------------------------------------------- /Chapter10/c10_21_ffMonthly.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter10/c10_21_ffMonthly.py -------------------------------------------------------------------------------- /Chapter10/c10_22_businessCycle.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter10/c10_22_businessCycle.R -------------------------------------------------------------------------------- /Chapter10/c10_23_logistic_reg.m: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter10/c10_23_logistic_reg.m -------------------------------------------------------------------------------- /Chapter10/c10_24_ddd.m: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter10/c10_24_ddd.m -------------------------------------------------------------------------------- /Chapter10/c10_25_ltfat.m: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter10/c10_25_ltfat.m -------------------------------------------------------------------------------- /Chapter10/c10_26_pca.m: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter10/c10_26_pca.m -------------------------------------------------------------------------------- /Chapter10/c10_27_Granger_test01.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter10/c10_27_Granger_test01.R -------------------------------------------------------------------------------- /Chapter10/c10_28_Granger_test02.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter10/c10_28_Granger_test02.R -------------------------------------------------------------------------------- /Chapter10/c10_29_catwalk_info.txt: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter10/c10_29_catwalk_info.txt -------------------------------------------------------------------------------- /Chapter10/c10_30_QuantEcon_simulated.jl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter10/c10_30_QuantEcon_simulated.jl -------------------------------------------------------------------------------- /Chapter10/c10_30_ltfat_example.m: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter10/c10_30_ltfat_example.m -------------------------------------------------------------------------------- /Chapter10/c10_31_timeUsed.jl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter10/c10_31_timeUsed.jl -------------------------------------------------------------------------------- /Chapter11/c11_01_qt_consol.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter11/c11_01_qt_consol.py -------------------------------------------------------------------------------- /Chapter11/c11_02_myfincal.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter11/c11_02_myfincal.py -------------------------------------------------------------------------------- /Chapter11/c11_03_dir_fincal.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter11/c11_03_dir_fincal.py -------------------------------------------------------------------------------- /Chapter12/c12_01_lapply.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter12/c12_01_lapply.R -------------------------------------------------------------------------------- /Chapter12/c12_02_parallel_01.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter12/c12_02_parallel_01.R -------------------------------------------------------------------------------- /Chapter12/c12_03_makeCluster.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter12/c12_03_makeCluster.R -------------------------------------------------------------------------------- /Chapter12/c12_04_parallel04.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter12/c12_04_parallel04.R -------------------------------------------------------------------------------- /Chapter12/c12_05_snow_01.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter12/c12_05_snow_01.R -------------------------------------------------------------------------------- /Chapter12/c12_06_plyr_example.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter12/c12_06_plyr_example.R -------------------------------------------------------------------------------- /Chapter12/c12_07_snow_parallel_Rmpi_UNIX.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter12/c12_07_snow_parallel_Rmpi_UNIX.R -------------------------------------------------------------------------------- /Chapter12/c12_08_pwordfreq.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter12/c12_08_pwordfreq.py -------------------------------------------------------------------------------- /Chapter12/c12_09_pwordfreq.txt: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter12/c12_09_pwordfreq.txt -------------------------------------------------------------------------------- /Chapter12/c12_10_plyr_arrange.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter12/c12_10_plyr_arrange.R -------------------------------------------------------------------------------- /Chapter12/c12_11_wordfreq.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter12/c12_11_wordfreq.py -------------------------------------------------------------------------------- /Chapter12/c12_12_pi_01.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter12/c12_12_pi_01.py -------------------------------------------------------------------------------- /Chapter12/c12_13_parallel.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter12/c12_13_parallel.R -------------------------------------------------------------------------------- /Chapter12/c12_14_pi_02.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter12/c12_14_pi_02.py -------------------------------------------------------------------------------- /Chapter12/c12_15_Monte Carlo Options.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter12/c12_15_Monte Carlo Options.ipynb -------------------------------------------------------------------------------- /Chapter12/c12_16_Monte Carlo Options.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter12/c12_16_Monte Carlo Options.ipynb -------------------------------------------------------------------------------- /Chapter12/c12_17_taskView.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter12/c12_17_taskView.R -------------------------------------------------------------------------------- /Chapter12/c12_18_taskview.txt: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter12/c12_18_taskview.txt -------------------------------------------------------------------------------- /Chapter12/c12_19_parallelpi.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter12/c12_19_parallelpi.py -------------------------------------------------------------------------------- /Chapter12/c12_20_parallelpi.txt: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter12/c12_20_parallelpi.txt -------------------------------------------------------------------------------- /Chapter12/c12_21_pidigits.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter12/c12_21_pidigits.py -------------------------------------------------------------------------------- /Chapter12/c12_22_pidigits.txt: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter12/c12_22_pidigits.txt -------------------------------------------------------------------------------- /Chapter12/c12_23_pwordfreq.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter12/c12_23_pwordfreq.py -------------------------------------------------------------------------------- /Chapter12/c12_24_pwordfreq.txt: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter12/c12_24_pwordfreq.txt -------------------------------------------------------------------------------- /Chapter12/c12_25_wordfreq_same_as_c12_11.txt: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Chapter12/c12_25_wordfreq_same_as_c12_11.txt -------------------------------------------------------------------------------- /Errata_03_52.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Errata_03_52.png -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/LICENSE -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/README.md -------------------------------------------------------------------------------- /Software and Hardware list.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Hands-On-Data-Science-with-Anaconda/HEAD/Software and Hardware list.pdf --------------------------------------------------------------------------------