import numpy as np
import pandas as pd
data = pd.read_csv('weather_data.csv')
data
data.shape
Data has 7 Rows and Columns
data.info()
data
data = data.replace(-99999,value=np.NaN)
data
data.info()
Now we have 2 missing values in temperature and windspeed column respectively
data
data = data.replace([32.0,7.0],value=99)
data
data
data.replace({'temperature':99.0,'windspeed':np.nan,'event':'0'},100)
data
data = data.replace({np.nan:69,'0':'Sunny'})
data
data = pd.read_csv('weather2.csv')
data
mph
from windspeed & F
from Temperature¶data = data.replace({'temperature':'[A-Za-z]','windspeed':'[A-Za-z]'},'',regex=True)
data
d = {'score':['exceptional','average','good','poor','average','exceptional'],
'student':['Karan','Arpit','Varun','Robin','Akshay','Ankush']}
data = pd.DataFrame(d)
data
data = data.replace(['poor','average','good','exceptional'],[1,2,3,4])
data