Pandas 根据另一列填充列中的空单元格

Question

A dataframe looks like this, and I want to fill the empty cells in the 'Date' column (when the "Area" is West or North), with content in "Year" column plus "0601".

Wanted result is as follows:

What I have tried:

from io import StringIO
import pandas as pd


csvfile = StringIO(
"""
Name    Area    Date    Year
David   West        2014
Mike    North   20220919    2022
Kate    West        2017
Lilly   East    20221226    2022
Peter   North   20221226    2022
Cara    Middle      2016

""")

df = pd.read_csv(csvfile, sep = '\t', engine='python')


L1 = ['West','North']
m1 = df['Date'].isnull()
m2 = df['Area'].isin(L1)

df['Date'] = df['Date'].mask(m1 & m2, df['Year'] + '0601')      # Try_1

df['Date'] = np.where(np.where(m1 & m2, df['Year'] + '0601'))   # Try_2

Both Try_1 and Try_2 pop the same error.

What's the right way to write the lines? Thank you.

Traceback (most recent call last):
  File "C:\Python38\lib\site-packages\pandas\core\ops\array_ops.py", line 142, in _na_arithmetic_op
    result = expressions.evaluate(op, left, right)
  File "C:\Python38\lib\site-packages\pandas\core\computation\expressions.py", line 235, in evaluate
    return _evaluate(op, op_str, a, b)  # type: ignore[misc]
  File "C:\Python38\lib\site-packages\pandas\core\computation\expressions.py", line 69, in _evaluate_standard
    return op(a, b)
numpy.core._exceptions.UFuncTypeError: ufunc 'add' did not contain a loop with signature matching types (dtype('<U21'), dtype('<U21')) -> dtype('<U21')

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "C:\My Documents\Scripts\(Desktop) WSS 20200323\GG.py", line 336, in <module>
    df['Date'] = np.where(np.where(m1 & m2, df['Year'] + '0601'))                   # try 2
  File "C:\Python38\lib\site-packages\pandas\core\ops\common.py", line 65, in new_method
    return method(self, other)
  File "C:\Python38\lib\site-packages\pandas\core\arraylike.py", line 89, in __add__
    return self._arith_method(other, operator.add)
  File "C:\Python38\lib\site-packages\pandas\core\series.py", line 4998, in _arith_method
    result = ops.arithmetic_op(lvalues, rvalues, op)
  File "C:\Python38\lib\site-packages\pandas\core\ops\array_ops.py", line 189, in arithmetic_op
    res_values = _na_arithmetic_op(lvalues, rvalues, op)
  File "C:\Python38\lib\site-packages\pandas\core\ops\array_ops.py", line 149, in _na_arithmetic_op
    result = _masked_arith_op(left, right, op)
  File "C:\Python38\lib\site-packages\pandas\core\ops\array_ops.py", line 111, in _masked_arith_op
    result[mask] = op(xrav[mask], y)
numpy.core._exceptions.UFuncTypeError: ufunc 'add' did not contain a loop with signature matching types (dtype('<U21'), dtype('<U21')) -> dtype('<U21')

Answer 1

You example works find, provided you have strings:

csvfile = StringIO("""
Name    Area        Date    Year
David   West         NaN    2014
Mike    North   20220919    2022
Kate    West         NaN    2017
Lilly   East    20221226    2022
Peter   North   20221226    2022
Cara    Middle       NaN    2016
""")

df = pd.read_csv(csvfile, sep = '\s+', engine='python', dtype='str')


L1 = ['West','North']
m1 = df['Date'].isnull()
m2 = df['Area'].isin(L1)

df['Date'] = df['Date'].mask(m1 & m2, df['Year'] + '0601')

print(df)

If year is not a string:

df['Date'] = df['Date'].mask(m1 & m2, df['Year'].astype(str) + '0601')

Output:

    Name    Area      Date  Year
0  David    West  20140601  2014
1   Mike   North  20220919  2022
2   Kate    West  20170601  2017
3  Lilly    East  20221226  2022
4  Peter   North  20221226  2022
5   Cara  Middle       NaN  2016

If you have numeric data:

df['Date'] = df['Date'].mask(m1 & m2, df['Year'].mul(10000) + 601)

Output:

    Name    Area        Date  Year
0  David    West  20140601.0  2014
1   Mike   North  20220919.0  2022
2   Kate    West  20170601.0  2017
3  Lilly    East  20221226.0  2022
4  Peter   North  20221226.0  2022
5   Cara  Middle         NaN  2016