pandas Sharing Tips for Filling Missing Value Columns with Mean Value
- 2021-07-09 08:42:23
- OfStack
pd. DataFrame usually contains many features. Sometimes, every column with missing values needs to be filled with mean value. The code implementation can be as follows:
for column in list(df.columns[df.isnull().sum() > 0]):
mean_val = df[column].mean()
df[column].fillna(mean_val, inplace=True)
# ------- Code decomposition -------
# Determine which columns have missing values and get series Object
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
...
# According to 1 Step results, filter the columns to be populated
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')