Update README.md

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# Employee Turnover Prediction code # Employee Turnover Prediction code
#import the Libraries
import numpy as np
import pandas as pd
import sys
import sklearn
import matplotlib
import matplotlib.pyplot as plt
%matplotlib inline
import seaborn as sns
#load and display the shape of the dataset.
df = pd.read_csv("WA_Fn-UseC_-HR-Employee-Attrition.csv")
print("The Shape of the dataset is : ", df.shape)
#first 5 rows of the df
df.head()
#last 5 rows of the df
df.tail()
#info about the features/columns in df
df.info()
# Values distribution of the label column (target) in df
df["Attrition"].value_counts()
#statistical info about the numeric columns
df.describe()
# check missing values in df ?
print('Sum of Missing values in the dataset:')
df.isna().sum()
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