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Quick introduction and training in Pandas, StatsModels, Scikit-Learn, NumPy and SciPy done in Jupyter Notebook

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.gitignore
 
 
01_pandas_introduction.ipynb
01_pandas_introduction.ipynb
 
 
02_statistical_tests_introduction.ipynb
02_statistical_tests_introduction.ipynb
 
 
03_normality_tests.ipynb
03_normality_tests.ipynb
 
 
04_t_tests.ipynb
04_t_tests.ipynb
 
 
05_nonparametric_tests.ipynb
05_nonparametric_tests.ipynb
 
 
06_anova.ipynb
06_anova.ipynb
 
 
07_data_analysis_introduction.ipynb
07_data_analysis_introduction.ipynb
 
 
08_data_preprocessing.ipynb
08_data_preprocessing.ipynb
 
 
09_dataframes_operations.ipynb
09_dataframes_operations.ipynb
 
 
10_classification.ipynb
10_classification.ipynb
 
 
LICENSE
LICENSE
 
 
README.md
README.md
 
 
anova_data.zip
anova_data.zip
 
 
dane_do_list_3-5.zip
dane_do_list_3-5.zip
 
 
igrzyska.xlsx
igrzyska.xlsx
 
 
igrzyska_list_7.csv
igrzyska_list_7.csv
 
 
igrzyska_list_8.csv
igrzyska_list_8.csv
 
 
olympic_games_gender.png
olympic_games_gender.png
 
 
olympic_games_gender_not_pruned.png
olympic_games_gender_not_pruned.png
 
 
requirements.txt
requirements.txt
 
 

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data-science-toolkit

Quick introduction and training in Pandas

About

Quick introduction and training in Pandas, StatsModels, Scikit-Learn, NumPy and SciPy done in Jupyter Notebook

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Readme
MIT license
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