fill missing values in column pandas with mean
df.fillna(df.mean(), inplace=True)fill missing values in column pandas with mean
df.fillna(df.mean(), inplace=True)fillna with mean pandas
sub2['income'].fillna((sub2['income'].mean()), inplace=True)how to fill nan values with mean in pandas
df.fillna(df.mean())python pandas fillna
# importing pandas module
import pandas as pd
# making data frame from csv file
nba = pd.read_csv("nba.csv")
# replacing na values in college with No college
nba["College"].fillna("No College", inplace = True)
# OR
nba.College.fillna("No College", inplace = True)
print(nba)python fillna with mean in a dataframe
df["newColumName"] = df["originalColumnName"].fillna(df["originalColumnName"].mean())fillna pandas inplace
When inplace = True , the data is modified in place, which means it will return nothing and the dataframe is now updated. When inplace = False , which is the default, then the operation is performed and it returns a copy of the object. You then need to save it to something.Copyright © 2021 Codeinu
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