adding all files done so far

bayes-learning/seaborn-descr.py

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+import pandas as pd
+import os
+import matplotlib
+import matplotlib.pyplot as plt
+# from sklearn.preprocessing import StandardScaler
+from sklearn.model_selection import train_test_split
+import numpy as np
+from scipy.stats import trim_mean, kurtosis
+from scipy.stats.mstats import mode, gmean, hmean
+
+
+def linebreak():
+    """prints a line break to split up functions"""
+    print('\n ============================================== \n')
+
+
+matplotlib.rcParams['backend'] = 'TkAgg'
+plt.style.use('seaborn-dark-palette')
+
+path = os.getcwd()
+data_file = str('/data/Social_Network_Ads.csv')
+
+df = pd.read_csv(path + data_file)
+# df = pd.DataFrame(df)
+
+df = df.sample(frac=1).reset_index(drop=True)
+
+print('{} rows. {} cols.'.format(df.shape[0], df.shape[1]))
+
+linebreak()
+print(df.iloc[0:10, :])
+
+linebreak()
+X = df[['Age', 'EstimatedSalary']]
+y = df['Purchased'].to_frame()
+
+print('X equals:')
+print(X.iloc[0:5])
+linebreak()
+print('y equals:')
+print(y[0:5])
+linebreak()
+
+X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33)
+
+description = df.describe().drop(columns=['User ID'])
+
+description_grouped = df.groupby(['Purchased'])
+
+description_grouped_split = description_grouped['Age', 'EstimatedSalary']\
+    .describe().unstack()
+
+description_grouped_mode = description_grouped['Age'].apply(mode, axis=None)
+
+df_quartile_slary = df.groupby('Purchased')['EstimatedSalary']\
+    .quantile([.1, .5, .9])
+df_quartile_age = df.groupby('Purchased')['Age'].quantile([.1, .5, .9])
+
+df_trimmed_mean = description_grouped['Age', 'EstimatedSalary'].\
+    aggregate(trim_mean, .1)
+
+df_summary = description_grouped['Age', 'EstimatedSalary']\
+    .aggregate([np.median, np.std, np.mean, gmean, hmean])
+
+df_var = description_grouped['Age', 'EstimatedSalary'].var()
+
+df_null = df.isna().sum()
+
+print(description)
+linebreak()
+print(description_grouped_split)
+linebreak()
+print(description_grouped_mode)
+linebreak()
+print(df_quartile_slary)
+print(df_quartile_age)
+linebreak()
+print(df_trimmed_mean)
+linebreak()
+print(df_summary)
+linebreak()
+print(df_var)
+linebreak()
+print(df_null)