python - Pandas :在字符串列中填充占位符

Question

我正在使用如下所示的 pandas DataFrame:

df = pd.DataFrame(
    [['There are # people', '3', np.nan], ['# out of # people are there', 'Five', 'eight'],
     ['Only # are here', '2', np.nan], ['The rest is at home', np.nan, np.nan]])

导致:

    0                            1     2
0   There are # people           3     NaN
1   # out of # people are there  Five  eight
2   Only # are here              2     NaN
3   The rest is at home          NaN   NaN

我想用第 1 列和第 2 列中的不同字符串替换 # 占位符，导致:

0   There are 3 people
1   Five out of eight people are there
2   Only 2 are here
3   The rest is at home

我怎样才能做到这一点？

Answer 1

使用字符串格式

df=df.replace({'#':'%s',np.nan:'NaN'},regex=True)

l=[]

for x , y in df.iterrows():
    if  y[2]=='NaN' and y[1]=='NaN':
        l.append(y[0])
    elif y[2]=='NaN':
        l.append(y[0] % (y[1]))
    else:
        l.append(y[0] % (y[1], y[2]))
l
Out[339]: 
['There are 3 people',
 'Five out of eight people are there',
 'Only 2 are here',
 'The rest is at home']