Python 如何在循环中过滤多个数据帧？

我有很多数据帧，我想对它们应用相同的过滤器，而不必每次都复制粘贴过滤器条件

这是我目前的代码：

df_list_2019 = [df_spain_2019,df_amsterdam_2019, df_venice_2019, df_sicily_2019]

for data in df_list_2019:
    data = data[['host_since','host_response_time','host_response_rate',
             'host_acceptance_rate','host_is_superhost','host_total_listings_count',
              'host_has_profile_pic','host_identity_verified',
             'neighbourhood','neighbourhood_cleansed','zipcode','latitude','longitude','property_type','room_type',
             'accommodates','bathrooms','bedrooms','beds','amenities','price','weekly_price',
             'monthly_price','cleaning_fee','guests_included','extra_people','minimum_nights','maximum_nights',
             'minimum_nights_avg_ntm','has_availability','availability_30','availability_60','availability_90',
              'availability_365','number_of_reviews','number_of_reviews_ltm','review_scores_rating',
              'review_scores_checkin','review_scores_communication','review_scores_location', 'review_scores_value',
              'instant_bookable','is_business_travel_ready','cancellation_policy','reviews_per_month'
             ]]

但它不会对数据帧应用过滤器。我如何更改代码才能做到这一点

谢谢

过滤器（列选择）实际上应用于每个数据帧，您只需覆盖名称

数据

所指向的内容即可丢弃结果

您需要将结果存储在某个位置，例如列表

cols = ['host_since','host_response_time', ...]
filtered = [df[cols] for df in df_list_2019]

---

只要写入

var=new\u value

，就不会更改原始对象，而是让变量引用新对象

如果要从

df_list_2019

更改数据帧，必须使用

inplace=True

方法。在这里，您可以使用

drop

：

keep = set(['host_since','host_response_time','host_response_rate',
             'host_acceptance_rate','host_is_superhost','host_total_listings_count',
              'host_has_profile_pic','host_identity_verified',
             'neighbourhood','neighbourhood_cleansed','zipcode','latitude','longitude','property_type','room_type',
             'accommodates','bathrooms','bedrooms','beds','amenities','price','weekly_price',
             'monthly_price','cleaning_fee','guests_included','extra_people','minimum_nights','maximum_nights',
             'minimum_nights_avg_ntm','has_availability','availability_30','availability_60','availability_90',
              'availability_365','number_of_reviews','number_of_reviews_ltm','review_scores_rating',
              'review_scores_checkin','review_scores_communication','review_scores_location', 'review_scores_value',
              'instant_bookable','is_business_travel_ready','cancellation_policy','reviews_per_month'
             ])

for data in df_list_2019:
    data.drop(columns=[col for col in data.columns if col not in keep], inplace=True)

但是要小心，熊猫专家建议选择

df=df习惯用法到
df…（…，inplace=True）
，因为它允许链接操作。所以你应该问问自己，如果不能使用。无论如何，这一个应该适合你的要求