├── .gitattributes ├── .gitignore ├── Analyzing Police Activity with pandas ├── Codings │ ├── Chapter 1-Preparing the data for analysis.py │ ├── Chapter 2-Exploring the relationship between gender and policing.py │ ├── Chapter 3-Visual exploratory data analysis.py │ └── Chapter 4-Analyzing the effect of weather on policing.py ├── Datasets │ ├── police.csv │ └── weather.csv └── Notes │ ├── chapter1.pdf │ ├── chapter2.pdf │ ├── chapter3.pdf │ └── chapter4.pdf ├── Cleaning Data in Python ├── Codings │ ├── Chapter 1-Exploring your data.py │ ├── Chapter 2-Tidying data for analysis.py │ ├── Chapter 3-Combining data for analysis.py │ ├── Chapter 4-Cleaning data for analysis.py │ └── Chapter 5-Case study.py ├── Datasets │ ├── airquality.csv │ ├── dob_job_application_filings_subset.csv │ ├── ebola.csv │ ├── gapminder.csv │ ├── nyc_uber_2014.csv │ ├── tb.csv │ └── tips.csv └── Notes │ ├── ch1_slides.pdf │ ├── ch2_slides.pdf │ ├── ch3_slides.pdf │ ├── ch4_slides.pdf │ └── ch5_slides.pdf ├── Conda Essentials └── Codings │ ├── Chapter 1-Installing Packages.py │ ├── Chapter 2-Utilizing Channels.py │ ├── Chapter 3-Working with Environments.py │ └── Chapter 4-Case Study on Using Environments.py ├── Importing Data in Python (Part 1) ├── Codings │ ├── Chapter 1-Introduction and flat files.py │ ├── Chapter 2-Importing data from other file types.py │ └── Chapter 3-Working with relational databases in Python.py ├── Datasets │ ├── Chinook.sqlite │ ├── L-L1_LOSC_4_V1-1126259446-32.hdf5 │ ├── battledeath.xlsx │ ├── disarea.dta │ ├── ja_data2.mat │ ├── mnist_kaggle_some_rows.csv │ ├── sales.sas7bdat │ ├── seaslug.txt │ └── titanic_sub.csv └── Notes │ ├── ch2_pdf_slides.pdf │ ├── ch_1_slides.pdf │ └── ch_3_slides.pdf ├── Importing Data in Python (Part 2) ├── Codings │ ├── Chapter 1-Importing data from the Internet.py │ ├── Chapter 2-Interacting with APIs to import data from the web.py │ └── Chapter 3-Diving deep into the Twitter API.py ├── Datasets │ ├── latitude.xls │ ├── tweets3.txt │ └── winequality-red.csv └── Notes │ ├── ch_1_slides.pdf │ ├── ch_2_slides.pdf │ └── ch_3_slides.pdf ├── Interactive Data Visualization with Bokeh ├── Codings │ ├── Chapter 1-Basic plotting with Bokeh.py │ ├── Chapter 2-Layouts, Interactions, and Annotations.py │ ├── Chapter 3-Building interactive apps with Bokeh.py │ └── Chapter 4-Putting It All Together! A Case Study.py ├── Datasets │ ├── aapl.csv │ ├── auto-mpg.csv │ ├── gapminder_tidy.csv │ ├── glucose.csv │ ├── literacy_birth_rate.csv │ └── sprint.csv └── Notes │ ├── ch1_slides.pdf │ ├── ch2_slides.pdf │ ├── ch4_slides.pdf │ └── ch5_slides.pdf ├── Intermediate Python for Data Science ├── Codings │ ├── Chapter 1-Matplotlib │ │ ├── 1.py │ │ ├── 10.py │ │ ├── 11.py │ │ ├── 12.py │ │ ├── 2.py │ │ ├── 3.py │ │ ├── 4.py │ │ ├── 5.py │ │ ├── 6.py │ │ ├── 7.py │ │ ├── 8.py │ │ └── 9.py │ ├── Chapter 2-Dictionaries & Pandas │ │ ├── 1.py │ │ ├── 10.py │ │ ├── 11.py │ │ ├── 12.py │ │ ├── 13.py │ │ ├── 14.py │ │ ├── 15.py │ │ ├── 2.py │ │ ├── 3.py │ │ ├── 4.py │ │ ├── 5.py │ │ ├── 6.py │ │ ├── 7.py │ │ ├── 8.py │ │ └── 9.py │ ├── Chapter 3-Logic, Control Flow and Filtering │ │ ├── 1.py │ │ ├── 10.py │ │ ├── 11.py │ │ ├── 12.py │ │ ├── 2.py │ │ ├── 3.py │ │ ├── 4.py │ │ ├── 5.py │ │ ├── 6.py │ │ ├── 7.py │ │ ├── 8.py │ │ └── 9.py │ ├── Chapter 4-Loops │ │ ├── 1.py │ │ ├── 10.py │ │ ├── 11.py │ │ ├── 12.py │ │ ├── 2.py │ │ ├── 3.py │ │ ├── 4.py │ │ ├── 5.py │ │ ├── 6.py │ │ ├── 7.py │ │ ├── 8.py │ │ └── 9.py │ └── Chapter 5-Case Study Hacker Statistics │ │ ├── 1.py │ │ ├── 10.py │ │ ├── 2.py │ │ ├── 3.py │ │ ├── 4.py │ │ ├── 5.py │ │ ├── 6.py │ │ ├── 7.py │ │ ├── 8.py │ │ └── 9.py ├── Datasets │ ├── brics.csv │ ├── cars.csv │ └── gapminder.csv └── Notes │ ├── intermediate_python_ch1_slides.pdf │ ├── intermediate_python_ch2_slides.pdf │ ├── intermediate_python_ch3_slides.pdf │ ├── intermediate_python_ch4_slides.pdf │ └── intermediate_python_ch5_slides.pdf ├── Introduction to Data Visualization with Python ├── Codings │ ├── Chapter 1-Customizing plots.py │ ├── Chapter 2-Plotting 2D arrays.py │ ├── Chapter 3-Statistical plots with Seaborn.py │ └── Chapter 4- Analyzing time series and images.py ├── Datasets │ ├── auto-mpg.csv │ ├── percent-bachelors-degrees-women-usa.csv │ └── stocks.csv └── Notes │ ├── ch1_slides.pdf │ ├── ch2_slides.pdf │ ├── ch3_slides.pdf │ └── ch4_slides.pdf ├── Introduction to Python ├── Codings │ ├── Chapter 1-Introduction to Python │ │ ├── 1.py │ │ ├── 2.py │ │ ├── 3.py │ │ ├── 4.py │ │ ├── 5.py │ │ ├── 6.py │ │ ├── 7.py │ │ └── 8.py │ ├── Chapter 2-Python Lists │ │ ├── 1.py │ │ ├── 10.py │ │ ├── 2.py │ │ ├── 3.py │ │ ├── 4.py │ │ ├── 5.py │ │ ├── 6.py │ │ ├── 7.py │ │ ├── 8.py │ │ └── 9.py │ ├── Chapter 3-Functions and Packages │ │ ├── 1.py │ │ ├── 2.py │ │ ├── 3.py │ │ ├── 4.py │ │ ├── 5.py │ │ ├── 6.py │ │ └── 7.py │ └── Chapter 4-NumPy │ │ ├── 1.py │ │ ├── 10.py │ │ ├── 11.py │ │ ├── 12.py │ │ ├── 2.py │ │ ├── 3.py │ │ ├── 4.py │ │ ├── 5.py │ │ ├── 6.py │ │ ├── 7.py │ │ ├── 8.py │ │ └── 9.py ├── Datasets │ ├── baseball.csv │ └── fifa.csv └── Notes │ ├── ch1_slides.pdf │ ├── ch2_slides.pdf │ ├── ch3_slides.pdf │ └── ch4_slides.pdf ├── Introduction to Relational Databases in SQL ├── Codings │ ├── Chapter 1-Your first database.py │ ├── Chapter 2-Enforce data consistency with attribute constraints.py │ ├── Chapter 3-Uniquely identify records with key constraints.py │ └── Chapter 4-Glue together tables with foreign keys.py └── Notes │ ├── chapter1.pdf │ ├── chapter2.pdf │ ├── chapter3.pdf │ └── chapter4.pdf ├── Introduction to Shell for Data Science └── Shell codings │ ├── Chapter 1-Manipulating files and directories.py │ ├── Chapter 2-Manipulating data.py │ ├── Chapter 3-Combining tools.py │ ├── Chapter 4-Batch processing.py │ └── Chapter 5-Creating new tools.py ├── LICENSE ├── Manipulating DataFrames with pandas ├── Codings │ ├── Chapter 1-Extracting and transforming data.py │ ├── Chapter 2-Advanced indexing.py │ ├── Chapter 3-Rearranging and reshaping data.py │ ├── Chapter 4-Grouping data.py │ └── Chapter 5-Bringing it all together.py ├── Datasets │ ├── all_medalists.csv │ ├── gapminder_tidy.csv │ ├── pennsylvania2012_turnout.csv │ ├── pittsburgh2013.csv │ ├── sales.zip │ ├── titanic.csv │ └── users.csv └── Notes │ ├── Python For Data Science Cheat Sheet.pdf │ ├── ch1_slides.pdf │ ├── ch2_slides.pdf │ ├── ch3_slides.pdf │ ├── ch4_slides.pdf │ └── ch5_slides.pdf ├── Merging DataFrames with pandas ├── Codings │ ├── Chapter 1-Preparing data.py │ ├── Chapter 2-Concatenating data.py │ ├── Chapter 3-Merging data.py │ └── Chapter 4-Case Study - Summer Olympics.py ├── Datasets │ ├── Baby names.zip │ ├── GDP.zip │ ├── Sales.zip │ ├── Summer Olympic medals.zip │ ├── automobiles.csv │ ├── exchange.csv │ ├── oil_price.csv │ ├── pittsburgh2013.csv │ └── sp500.csv └── Notes │ ├── ch1_slides.pdf │ ├── ch2_slides.pdf │ ├── ch3_slides.pdf │ └── ch4_slides.pdf ├── Natural Language Processing Fundamentals in Python ├── Chapter 1-Regular expressions & word tokenization │ ├── 1.py │ ├── 2.py │ ├── 3.py │ ├── 4.py │ ├── 5.py │ ├── 6.py │ └── chapter1.pdf ├── Chapter 2-Simple topic identification │ ├── 1.py │ ├── 2.py │ ├── 3.py │ ├── 4.py │ ├── 5.py │ └── chapter2.pdf ├── Chapter 3-Named-entity recognition │ ├── 1.py │ ├── 2.py │ ├── 3.py │ ├── 4.py │ ├── 5.py │ ├── 6.py │ └── chapter3.pdf ├── Chapter 4-Building a fake news classifier │ ├── 1.py │ ├── 2.py │ ├── 3.py │ ├── 4.py │ ├── 5.py │ ├── 6.py │ ├── 7.py │ └── chapter4.pdf └── Datasets │ ├── News articles │ └── News articles │ │ ├── articles.txt │ │ ├── blaise.txt │ │ ├── french.txt │ │ └── uber_apple.txt │ ├── Wikipedia articles │ └── Wikipedia articles │ │ ├── wiki_text_bug.txt │ │ ├── wiki_text_computer.txt │ │ ├── wiki_text_crash.txt │ │ ├── wiki_text_debugger.txt │ │ ├── wiki_text_debugging.txt │ │ ├── wiki_text_exception.txt │ │ ├── wiki_text_hopper.txt │ │ ├── wiki_text_language.txt │ │ ├── wiki_text_malware.txt │ │ ├── wiki_text_program.txt │ │ ├── wiki_text_reversing.txt │ │ └── wiki_text_software.txt │ ├── english_stopwords.txt │ └── grail.txt ├── Python Data Science Toolbox (Part 1) ├── Chapter 1-Writing your own functions │ ├── 1.py │ ├── 2.py │ ├── 3.py │ ├── 4.py │ ├── 5.py │ ├── 6.py │ ├── 7.py │ ├── 8.py │ └── ch1_slides.pdf ├── Chapter 2-Default arguments, variable-length arguments and scope │ ├── 1.py │ ├── 10.py │ ├── 2.py │ ├── 3.py │ ├── 4.py │ ├── 5.py │ ├── 6.py │ ├── 7.py │ ├── 8.py │ ├── 9.py │ └── ch2_slides.pdf ├── Chapter 3-Lambda functions and error-handling │ ├── 1.py │ ├── 2.py │ ├── 3.py │ ├── 4.py │ ├── 5.py │ ├── 6.py │ ├── 7.py │ ├── 8.py │ ├── 9.py │ └── ch3_slides.pdf └── Datasets │ └── tweets.csv ├── Python Data Science Toolbox (Part 2) ├── Chapter 1-Using iterators in PythonLand │ ├── 1.py │ ├── 2.py │ ├── 3.py │ ├── 4.py │ ├── 5.py │ ├── 6.py │ ├── 7.py │ ├── 8.py │ └── ch1_slides.pdf ├── Chapter 2-List comprehensions and generators │ ├── 1.py │ ├── 10.py │ ├── 2.py │ ├── 3.py │ ├── 4.py │ ├── 5.py │ ├── 6.py │ ├── 7.py │ ├── 8.py │ ├── 9.py │ └── ch2_slides.pdf ├── Chapter 3-Bringing it all together! │ ├── 1.py │ ├── 10.py │ ├── 11.py │ ├── 12.py │ ├── 2.py │ ├── 3.py │ ├── 4.py │ ├── 5.py │ ├── 6.py │ ├── 7.py │ ├── 8.py │ ├── 9.py │ └── ch3_slides.pdf └── Datasets │ ├── tweets.csv │ └── world_ind_pop_data.csv ├── README.md ├── Statistical Thinking in Python (Part 1) ├── Codings │ ├── Chapter 1-Graphical exploratory data analysis.py │ ├── Chapter 2-Quantitative exploratory data analysis.py │ ├── Chapter 3-Thinking probabilistically-- Discrete variables.py │ └── Chapter 4-Thinking probabilistically-- Continuous variables.py ├── Datasets │ ├── 2008_all_states.csv │ ├── 2008_swing_states.csv │ ├── belmont.csv │ └── michelson_speed_of_light.csv └── Notes │ ├── ch1_slides.pdf │ ├── ch2_slides.pdf │ ├── ch3_slides.pdf │ └── ch4_slides.pdf ├── Statistical Thinking in Python (Part 2) ├── Codings │ ├── Chapter 1-Parameter estimation by optimization.py │ ├── Chapter 2-Bootstrap confidence intervals.py │ ├── Chapter 3 -Introduction to hypothesis testing.py │ ├── Chapter 4-Hypothesis test examples.py │ └── Chapter 5-Putting it all together- a case study.py ├── Datasets │ ├── anscombe.csv │ ├── bee_sperm.csv │ ├── female_literacy_fertility.csv │ ├── finch_beaks_1975.csv │ ├── finch_beaks_2012.csv │ ├── fortis_beak_depth_heredity.csv │ ├── frog_tongue.csv │ 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