Pandas common skills

dataframe["new_column"] = dataframe.apply(
    lambda row: row.exist_column * 2, axis=1)

df.drop('column_name', axis=1, inplace=True)

inplace 代表修改 df, 不用重新创建一个变量

删除多列

df.drop(['column_nameA', 'column_nameB'], axis=1, inplace=True)

dataframe.drop(dataframe[dataframe.location_ts.isnull()].index, inplace=True)

 df[df['A'].isin([3, 6])]

we can use map to update dataframe data by dict:

df['A'] = df['A'].map({'a': 1, 'b': 2, 'c': 3})

if A column has value not in dict, it will be NaN, and it will raise error when serializing, so we need to give map a default value:

df['A'] = df['A'].map(lambda x: {'a': 1, 'b': 2, 'c': 3}.get(x, 0))

all_df = all_df.fillna(0)

dataframe.column_filed.isnull()