pandas replace nan
data["Gender"].fillna("No Gender", inplace = True)pandas replace nan
data["Gender"].fillna("No Gender", inplace = True)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)replace nan using fillna
>>> df.fillna(method='ffill')
A B C D
0 NaN 2.0 NaN 0
1 3.0 4.0 NaN 1
2 3.0 4.0 NaN 5
3 3.0 3.0 NaN 4fillna 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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