python - 应用if语句替换 'Column Y'中不同行对应的 'Column X'中的数据

Question

下面是我正在处理的一部分数据，其中有数千行和其他列。我必须根据“X 列”中的以下条件更改“Y 列”中的值。

如果第 X 列是“第一个”:

细胞#1 = 上皮细胞

细胞#2 = 神经

如果 X 列是“SECOND”:

细胞#1 = 内皮细胞

细胞#2 = 肌肉

数据框:

 Column X            Column Y        
    FIRST               cell#1
    FIRST               A
    FIRST               cell#2
    FIRST               C
    SECOND              N
    SECOND              V
    SECOND              cell#1
    SECOND              cell#2

代码:

for row in df['Column X']:
    if row == "FIRST":
        df.loc[(df['Column Y']== "cell#1"), 'Column Y'] = "epithelial"
        df.loc[(df['Column Y']== "cell#2"), 'Column Y'] = "nerve"
    elif row == "SECOND":
        df.loc[(df['Column Y']== "cell#1"), 'Column Y'] = "endothelial"
        df.loc[(df['Column Y']== "cell#2"), 'Column Y'] = "muscle"
    else:
        pass

我上面的代码不起作用，rows=='FIRST' 的条件适用于整个数据帧，并忽略 rows=='SECOND' 的条件。请帮助。

预期结果:

Column X            Column Y        
    FIRST               epithelial
    FIRST               A
    FIRST               nerve
    FIRST               C
    SECOND              N
    SECOND              V
    SECOND              endothelial
    SECOND              muscle

我上面代码的输出(不正确):

Column X            Column Y        
    FIRST               epithelial
    FIRST               A
    FIRST               nerve
    FIRST               C
    SECOND              N
    SECOND              V
    SECOND              epithelial
    SECOND              nerve

Y 列的最后两行应该是“内皮”和“肌肉”，而不是“上皮”和“神经”

Answer 1

这是一种方式。请注意，不需要循环。许多 pandas 操作都经过矢量化处理，以提高易用性和性能。

import pandas as pd

df = pd.DataFrame([['FIRST', 'cell#1'], ['FIRST', 'A'],
                   ['FIRST', 'cell#2'], ['FIRST', 'C'],
                   ['SECOND', 'N'], ['SECOND', 'V'],
                   ['SECOND', 'cell#1'], ['SECOND', 'cell#2']],
                  columns=['X', 'Y'])

df.loc[(df.X == 'FIRST') & (df.Y == 'cell#1'), 'Y'] = 'epithelial'
df.loc[(df.X == 'FIRST') & (df.Y == 'cell#2'), 'Y'] = 'nerve'
df.loc[(df.X == 'SECOND') & (df.Y == 'cell#1'), 'Y'] = 'endothelial'
df.loc[(df.X == 'SECOND') & (df.Y == 'cell#2'), 'Y'] = 'muscle'

#         X            Y
# 0   FIRST   epithelial
# 1   FIRST            A
# 2   FIRST        nerve
# 3   FIRST            C
# 4  SECOND            N
# 5  SECOND            V
# 6  SECOND  endothelial
# 7  SECOND       muscle