在 Pandas 将 colum1 值与 colum2 合并时，col 数据类型都是 object 并且第一列中只有少数值是 null？

Question

Data Frame is having two columns Data Frame is having two columns

df1
col1 col2
 A    A
 B    A 
 B    A
 C    B
      C
      D
      E
 E    E
 F    G
      G
      H
      H

here both columns are object type, trying to merge value of column 2 with column 1 where column 1 value is null. how to apply this for large dataset?I'm beginner for panads, trying to learn all the tricks here.

Expected output:

col1 col2
 A    A
 B    A 
 B    A
 C    B
 C    C
 D    D
 E    E
 E    E
 F    G
 G    G
 H    H
 H    H

Answer 1

You can also use np.where .

df['col1'] = np.where(df['col1'], df['col1'], df['col2'])

Or combine_first after first ensuring empty strings are represented as null values.

df['col1'] = df['col1'].replace('', np.nan).combine_first(df['col2'])

Answer 2

If empty values are missing values:

print (df)
  col1 col2
0    A    A
1    B    B
2  NaN    C
3  NaN    D
4  NaN    E
5    E    E
6    F    F
7  NaN    G
8  NaN    H
9  NaN    H

df['col1'] = df['col1'].fillna(df['col2'])
print (df)
  col1 col2
0    A    A
1    B    B
2    C    C
3    D    D
4    E    E
5    E    E
6    F    F
7    G    G
8    H    H
9    H    H

If empty values are empty strings:

print (df)
  col1 col2
0    A    A
1    B    B
2         C
3         D
4         E
5    E    E
6    F    F
7         G
8         H
9         H

df['col1'] = df['col1'].mask(df['col1'] == '', df['col2'])
#thanks U10-Forward 
df['col1'] = f['col1'].replace('', np.nan).fillna(df['col2'])
print (df)
  col1 col2
0    A    A
1    B    B
2    C    C
3    D    D
4    E    E
5    E    E
6    F    F
7    G    G
8    H    H
9    H    H