import numpy as np
import pandas as pd

df =pd.read_csv('3rd progrma.csv')
df

df.head()

df.tail()

df.describe()

df.info()


df.isnull().sum()

df.drop("name",axis=1,inplace=True)
df

df.drop(10,axis=0,inplace=True)
df

df["age"]=df["age"].fillna(df["age"].mean())
df

df["salary"]=df["salary"].fillna(df["salary"].max())
df

df.drop_duplicates()

x=np.array(df)[:,:-1]
x
y=np.array(df)[:,-1]
y

from sklearn.compose import ColumnTransformer
from sklearn.preprocessing import OneHotEncoder
ct=ColumnTransformer(transformers=[('encoder',OneHotEncoder(),[0])],remainder="passthrough")
x=np.array(ct.fit_transform(x))
x

from sklearn.preprocessing import(incomplete code)