text_plain_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 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()

sns.kdeplot(data=bdata, x='age', hue='loan')