import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import OneHotEncoder
from sklearn.compose import ColumnTransformer
sns.set()

df = pd.read_csv("50_Startups.csv")

def null_table(data):
    null_values = data.isnull().sum().sort_values(ascending=False)
    percentage = (data.isnull().sum()/data.isnull().count()).sort_values(ascending= False)
    missing_data = pd.concat([null_values,percentage],keys=["Total","Percentage"], axis=1)
    return missing_data