Learn practical skills, build real-world projects, and advance your career
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import pandas_profiling as pp
from scipy import stats
from sklearn.linear_model import LogisticRegression
from sklearn.metrics import accuracy_score
from sklearn.metrics import f1_score
from sklearn.metrics import recall_score 
from sklearn.metrics import precision_score

pd.set_option('display.max_rows', 500)
pd.set_option('display.max_columns', 500)
pd.set_option('display.width', 1000)

df = pd.read_csv('telecom_churn_data.csv')
import warnings
warnings.filterwarnings('ignore')
df.shape
(99999, 226)

Original Dataset has 99999 rows and 226 columns

df.head()