Question

我有一个城市名称列表和一个带有城市，州和邮政编码列的df。缺少一些邮政编码。如果缺少邮政编码，我想使用基于城市的通用邮政编码。例如，城市为圣何塞，因此邮政编码应为通用的“ SJ_zipcode”。

pattern_city = '|'.join(cities) #works

foundit = ( (df['cty_nm'].str.contains(pattern_city, flags=re.IGNORECASE)) & (df['zip_cd']==0) & (df['st_cd'].str.match('CA') ) ) #works--is this foundit a df?

df['zip_cd'] = foundit.replace( 'SJ_zipcode' ) #nope, error

错误：“ pad_1d [bool]的dtype无效”

以where

开头

df['zip_cd'].where( (df['cty_nm'].str.contains(pattern_city, flags=re.IGNORECASE)) & (df['zip_cd']==0) & (df['st_cd'].str.match('CA') ), "SJ_Zipcode", inplace = True) #nope, empty set; all set to nan?

以loc

开头

df['zip_cd'].loc[ (df['cty_nm'].str.contains(pattern_city, flags=re.IGNORECASE)) & (df['zip_cd']==0) & (df['st_cd'].str.match('CA') ) ] = "SJ_Zipcode"

一些可能不可行的解决方案

df.loc[df['First Season'] > 1990, 'First Season'] = 1，我曾经使用过df.loc[foundit, 'zip_cd'] = 'SJ_zipcode' Pandas DataFrame: replace all values in a column, based on condition，与Conditional Replace Pandas类似/相同
df['c'] = df.apply( lambda row: row['a']*row['b'] if np.isnan(row['c']) else row['c'], axis=1)，但是，我不乘数值https://datascience.stackexchange.com/questions/17769/how-to-fill-missing-value-based-on-other-columns-in-pandas-dataframe
我尝试使用where解决方案，但是，它似乎用nan代替了不满足条件的值，但是nan值并没有帮助https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.where.html
这种有条件的方法看起来很有希望，但是随后却没有重复每个值，我对事情的发生感到困惑……What should replace comparisons with False in python?
使用replace的示例，其中没有多个条件和模式Replacing few values in a pandas dataframe column with another value

另一个“想要”；我想用值更新数据框，我不想创建新的数据框。

Answer 1

尝试一下：

df = pd.DataFrame(data)
df

    city         state        zip
0   Burbank      California   44325
1   Anaheim      California   nan
2   El Cerrito   California   57643
3   Los Angeles  California   56734
4   san Fancisco California   32819

def generate_placeholder_zip(row):
    if pd.isnull(row['zip'] ):
        row['zip'] =row['city']+'_ZIPCODE'
    return row   

df.apply(generate_placeholder_zip, axis =1)

    city          state         zip
0   Burbank       California    44325
1   Anaheim       California    Anaheim_ZIPCODE
2   El Cerrito    California    57643
3   Los Angeles   California    56734
4   san Fancisco  California    32819

满足条件时更新或替换df中的值

1 个答案: