for column in list(df.columns[df.isnull().sum() > 0]):
  mean_val = df[column].mean()
  df[column].fillna(mean_val, inplace=True)

# -------代码分解-------
# 判断哪些列有缺失值，得到series对象
df.isnull().sum() > 0
# output
contributors           True
coordinates            True
created_at            False
display_text_range        False
entities             False
extended_entities         True
favorite_count          False
favorited            False
full_text            False
geo                True
id                False
id_str              False
...

# 根据上一步结果，筛选需要填充的列
df.columns[df.isnull().sum() > 0]
# output
Index(['contributors', 'coordinates', 'extended_entities', 'geo',
    'in_reply_to_screen_name', 'in_reply_to_status_id',
    'in_reply_to_status_id_str', 'in_reply_to_user_id',
    'in_reply_to_user_id_str', 'place', 'possibly_sensitive',
    'possibly_sensitive_appealable', 'quoted_status', 'quoted_status_id',
    'quoted_status_id_str', 'retweeted_status'],
   dtype='object')