text_plain_output_1.png image_output_1.png
import matplotlib.pyplot as plt #for data visualization.

import os

import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)

import random

import seaborn as sns

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
sns.set(rc={'figure.figsize': (14, 7)})
import random
from scipy import stats
import math
import os

bdata = pd.read_csv('../input/bank-marketing/bank-additional-full.csv', sep=';')

bdata.job.value_counts()

bdata.job.value_counts()

palette = sns.color_palette('bright')

for col in bdata.select_dtypes('object'):
    palette_color = sns.color_palette('bright')
    bdata[col].value_counts().plot.pie(colors=palette_color, autopct='%.0f%%')
    plt.figure()