如何根据已定义的模式转换数据框架

Question

我想要一个数据框恰好有这些列:

columns=['index', 'count_1','count_2', 'count_3', 'count_4', 'count_5']

因此，如果给定的数据框没有，例如'count_2'，我想将count_2添加到所有值为0的数据框中

如果这个数据框有其他列不在columns列表中，我想删除整个列。

的例子:输入dataframe:

'index' 'count_1','count_2' 'count_3' 'count_4' 'count_5'
1        10        12        45        0        23

是好的!

dataframe:

'index' 'count_1', 'count_3' 'count_4' 'count_5'
1        10         45        0        23

应该转换为:

'index' 'count_1','count_2' 'count_3' 'count_4' 'count_5'
1        10        0        45        0        23

dataframe

'index' 'count_1','count_2' 'count_3' 'count_4' 'count_5'   'count_6'
1        10        0        45        0        23          11

应该转换为:

index' 'count_1','count_2' 'count_3' 'count_4' 'count_5'
1        10        0        45        0        23

Answer 1

每列使用DataFrame.reindex，将缺失的值替换为0:

columns=['index', 'count_1','count_2', 'count_3', 'count_4', 'count_5']
df = df.reindex(columns=columns, fill_value=0)