├── Session1 ├── concat year month day and product permutation.ipynb ├── df.clipboard_convert table to df.ipynb ├── dropna threshold percentage row and column.ipynb ├── filter by groupby.ipynb ├── get rid of Unnamed in df.ipynb ├── groupby agg multindex drop level.ipynb ├── insert and change column order in pandas.ipynb └── regex eliminate string and convert string to float.ipynb ├── Session2 ├── If_Reads_Numerical_Values_As_Object_-_pandas.read_csv.ipynb ├── Quick_One-Hot_Encoding_with_Pandas.ipynb ├── Quick_Web_Scraping_with_Pandas.ipynb ├── create others values in pandas column.ipynb ├── map function and assign numbers to category (factorize) and boolean.ipynb └── select columns by slicing pandas.ipynb ├── Session3 ├── Deal_with_zip_files.ipynb ├── Parquet_and_Pickle_instead_of_CSV.ipynb ├── count words in row.ipynb ├── pd.cut pd.qcut.ipynb ├── query_Dataframe.ipynb └── transform sum pandas column.ipynb ├── Session4 ├── load autotime for every cell runtime and select_dtypes.ipynb └── swifter apply fastest run.ipynb └── Session5 ├── pd.to_numeric errors coerce.ipynb └── random create dataframe.ipynb /Session1/concat year month day and product permutation.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/DataScientistsArena/Pandas-Tricks/HEAD/Session1/concat year month day and product permutation.ipynb -------------------------------------------------------------------------------- /Session1/df.clipboard_convert table to df.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/DataScientistsArena/Pandas-Tricks/HEAD/Session1/df.clipboard_convert table to df.ipynb -------------------------------------------------------------------------------- /Session1/dropna threshold percentage row and column.ipynb: -------------------------------------------------------------------------------- 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