更新或替换DF中的值，当条件为m时

Question

我有一个城市名称列表和一个带有城市、州和zipcode列的df。一些zipcodes丢失了。当zipcode丢失时，我想使用基于城市的通用zipcode。例如，城市是圣何塞，因此zipcode应该是一个通用的“SJïu zipcode”。你知道吗

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\u 1d[bool]的数据类型无效”

用where实现

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?

用loc实现

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"

一些可能的解决方案不起作用

• df.loc[df['First Season'] > 1990, 'First Season'] = 1我用它作为df.loc[foundit, 'zip_cd'] = 'SJ_zipcode'Pandas DataFrame: replace all values in a column, based on condition和Conditional Replace Pandas相似/相同
• df['c'] = df.apply( lambda row: row['a']*row['b'] if np.isnan(row['c']) else row['c'], axis=1)但是，我不是在乘以值https://datascience.stackexchange.com/questions/17769/how-to-fill-missing-value-based-on-other-columns-in-pandas-dataframe
• 我尝试了一个使用where的解决方案，但是，它似乎替换了nan不满足条件的值--但是nan值没有帮助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，但是如果没有循环每个值，我就被什么事情是怎么发生的弄糊涂了。。。What should replace comparisons with False in python?
• 一个使用replace的例子，它没有多个条件和模式Replacing few values in a pandas dataframe column with another value

一个额外的'want'；我想用值更新一个数据帧，我不想创建一个新的数据帧。你知道吗

Answer 1

试试这个：

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