Question

我很遗憾有一个问题，一些帮助或提示将不胜感激。

问题：我有一个带有列的csv文件，可能有多个值，如：

public

我已将数据加载到数据框中，我需要根据“The_evil_column”列的值将该数据框拆分为多个数据框：

Fruit;Color;The_evil_column
Apple;Red;something1
Apple;Green;something1
Orange;Orange;something1
Orange;Green;something2
Apple;Red;something2
Apple;Red;something3

在阅读了一些帖子后，我更加困惑，我需要一些关于此的提示。

Answer 1

您可以生成DataFrames字典：

d = {g:x for g,x in df.groupby('The_evil_column')}

In [95]: d.keys()
Out[95]: dict_keys(['something1', 'something2', 'something3'])

In [96]: d['something1']
Out[96]:
    Fruit   Color The_evil_column
0   Apple     Red      something1
1   Apple   Green      something1
2  Orange  Orange      something1

或DataFrames列表：

In [103]: l = [x for _,x in df.groupby('The_evil_column')]

In [104]: l[0]
Out[104]:
    Fruit   Color The_evil_column
0   Apple     Red      something1
1   Apple   Green      something1
2  Orange  Orange      something1

In [105]: l[1]
Out[105]:
    Fruit  Color The_evil_column
3  Orange  Green      something2
4   Apple    Red      something2

In [106]: l[2]
Out[106]:
   Fruit Color The_evil_column
5  Apple   Red      something3

<强>更新

In [111]: g = pd.read_csv(filename, sep=';').groupby('The_evil_column')

In [112]: g.ngroups   # number of unique values in the `The_evil_column` column
Out[112]: 3

In [113]: g.apply(lambda x: x.to_csv(r'c:\temp\{}.csv'.format(x.name)))
Out[113]:
Empty DataFrame
Columns: []
Index: []

将生成3个文件：

In [115]: glob.glob(r'c:\temp\something*.csv')
Out[115]:
['c:\\temp\\something1.csv',
 'c:\\temp\\something2.csv',
 'c:\\temp\\something3.csv']

Answer 2

您只需按列的值过滤框架：

frame=pd.read_csv('file.csv',delimiter=';')
frame['The_evil_column']=='something1'

返回：

0     True
1     True
2     True
3    False
4    False
5    False
Name: The_evil_column, dtype: bool

因此，您可以访问以下列：

frame1 = frame[frame['The_evil_column']=='something1']

稍后您可以删除列：

frame1 = frame1.drop('The_evil_column', axis=1)

Answer 3

更简单但效率更低的方法是：

data = pd.read_csv('input.csv')

out = []

for evil_element in list(set(list(data['The_evil_column']))):
    out.append(data[data['The_evil_column']==evil_element])

out将包含所有数据数据框的列表。

Pandas通过列将CSV拆分为多个CSV（或DataFrame）

3 个答案: