Data cleaning in python | how to clean data | 2024

code is here!!!!!!!
hii guys... i'm share you how to clean and customize the data....
it's vary important part for data analysis....and upcoming video will provide more techniques for the data cleaning....please connect from me...subscribe the channel....if any query ask in the comment box....

#load dataset
import pandas as pd
df = pd.read_excel("data.xlsx")

#let's find the duplicate rows and delete them...
df[df.duplicated()] #but which row is duplicate???

#let's drop it...
df.drop_duplicates(inplace=True,ignore_index=True)

# the nick_name column is not important for use let's go delete it
df.drop("Nick_name",axis = 1 ,inplace=True)

# see in name and state column contain multiple informatin in a single column...
#let's solve them....and divided into seperate columns...
df["Name"].str.split(",",expand=True) #return 2 vclomns...

#letsplay 's save in main dataframe...
df[["First_name","last_name"]]= df["Name"].str.split(",",expand=True)

# let's solve state column same as name column...
df[["State","Zip_code"]] = df["State"].str.split(",",expand=True)

# let's delete name column...
df.drop("Name",axis = 1,inplace=True)

#now you can se the Adhar_no. column....we need all number in this format:-- 1234-5678-1234 --:this
#let's solve that...
df["Adhar_no."].str.replace("-","") #replace - into nothing

#save into main dataframe...
df["Adhar_no."] = df["Adhar_no."].str.replace("-","")

#but there is more values seperated by spaces and comma...let's solve them...
df["Adhar_no."] = df["Adhar_no."].str.replace(" ","")
df["Adhar_no."] = df["Adhar_no."].str.replace(",","")
df
#but we need this format:-- 1234-5678-3456
#let's solve...
#we are using lambda function...ok

df["Adhar_no."]= df["Adhar_no."].apply(lambda x: x[0:4] + "-" + x[4:8] + "-" + x[8:12]) #this is slicing....ok friends...

# ok then now we are going to dealing with nan and null values...
#we can fill the na value by the mean of the column...
# ok let's solve...
df["Salary"]=df["Salary"].fillna(df["Salary"].mean())

#our dataset is cleaned....
#let's arranging the columns...ok..
df = pd.DataFrame({"First_name":df["First_name"],
"Last_name":df["last_name"],
"Age":df["Age"],
"Slary":df["Salary"],
"Adhar_no.":df["Adhar_no."],
"State":df["State"],
"Zip_code":df["Zip_code"]
})
df

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