Merge 2 Columns Into 1 Column

I will like to merge 2 columns into 1 column and remove nan. I have this data: Name A B Pikachu 2007 nan Pikachu nan 2008 Raichu 2007

Solution 1:

Use Series.fillna with DataFrame.pop for extract columns and last convert to integers:

df['Year']= df.pop('A').fillna(df.pop('B')).astype(int)

#if possible some missing values in Year column
#df['Year']= df.pop('A').fillna(df.pop('B')).astype('Int64')
print (df)
      Name  Year
0  Pikachu  2007
1  Pikachu  2008
2   Raichu  2007
3      Mew  2018

Solution 2:

Could you please try following.

df['Year']=df['A'].combine_first(df['B'])
df

Output will be as follows.

     Name    A       B      Year
0   Pikachu 2007.0  NaN     2007.0
1   Pikachu NaN     2008.0  2008.0
2   Raichu  2007.0  NaN     2007.0
3   Mew     NaN     2018.0  2018.0

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To get only Name and year columns in a new data frame try following.

df['Year']=df['A'].combine_first(df['B'])
df1=df[['Name','Year']]
df1

Solution 3:

df = df.fillna(0)
df["Year"] = df["A"] + df["B"]
df = df[['Name','Year']]

Solution 4:

numpy.where could be usefull

df["A"] = np.where(df["A"].isna(), df["B"], df["A"]).astype("int")
df = df.drop("B", axis=1)
print(df)
    Name    Year
0   Pikachu 2007
1   Pikachu 2008
2   Raichu  2007
3   Mew     2018