python - Pandas:获取具有列值的行并用另一个值更新注释列

Question

我有下面的数据框

       FQDN       ip address     verstatus        Comments
0     pp.xx.com   XX.XXX.XXX.XX   Developed           NaN
1     qq.xx.com   XX.XXX.XXX.XX   NaN                NaN
2     gg.xx.com   XX.XXX.XXX.XX   Reserve            NaN
3     gg.xx.com   XX.XXX.XXX.XX   Testing            NaN

所以当verstatus不等于“Developed”或“NaN”(其他任何东西)时我需要更新然后评论

所以预期的结果是

       FQDN       ip address     version status        Comments
0     pp.xx.com   XX.XXX.XXX.XX   Developed           NaN
1     qq.xx.com   XX.XXX.XXX.XX   NaN                NaN
2     gg.xx.com   XX.XXX.XXX.XX   Reserve            Reserve Status
3     gg.xx.com   XX.XXX.XXX.XX   Testing            Testing Status

我试过了

df['Comments'] = df.apply(lambda x: x["version status"]+" Status" if x['version status'] != 'Developed' or x['version status'].notna()  else x['Comments'], axis=1)

但它不能正常工作

Answer 1

.notna() 是一个 pandas 函数，但是 x['version status'] 是一个字符串，你应该使用 pd.isna 像这样:

df['Comments'] = df.apply(lambda x: x['Comments'] if x['version status']=='Developed' 
                                                     or pd.isna(x['version status']) 
                                                  else x["version status"]+" Status", 
                          axis=1)

我认为这样会更干净:

# version status is either Developed or nan
cond = df['verstatus'].eq('Developed') | df['verstatus'].isna()

# you can update with `np.where`
df['Comments'] = np.where(cond, df['Comments'], df['verstatus'] + ' Status')