将最后一个非 nAn 值替换为数据帧的最后一列

Question

My current dataframe is this:

df.head()

Output:

Name	Gender	Country	Year
Adam	Male	America	1993
Betty	1968	NaN	NaN
Calvin	NaN	1995	NaN
Debra	Female	2000	NaN

I would like to shift all the last non-NaN values to the last column of the dataframe.

• Every row will have the year in the last non-NaN column of the dataframe
• What every row definitely has is the 'Name' and 'Year' value
• The 'Year' value could be either in Gender or Country column

So basically I need a code that populates this output:

Output:

Name	Gender	Country	Year
Adam	Male	America	1993
Betty	NaN	NaN	1968
Calvin	NaN	NaN	1995
Debra	Female	NaN	2000

Thank you for your help

Answer 1

Use ffill on index axis because Year is your last column and the last valid value of a row is a year.

df['Year'] = df.ffill(axis=1)['Year'].astype(int)
print(df)

# Output
     Name  Gender  Country  Year
0    Adam    Male  America  1993
1   Betty    1968      NaN  1968
2  Calvin     NaN     1995  1995
3   Debra  Female     2000  2000

To be safe, you can use pd.to_numeric to remove values where year is not defined for a row:

df['Year'] = pd.to_numeric(df.ffill(axis=1)['Year'], errors='coerce')
print(df)

# Output
     Name  Gender  Country    Year
0    Adam    Male  America  1993.0
1   Betty    1968      NaN  1968.0
2  Calvin     NaN     1995  1995.0
3   Debra  Female     2000  2000.0