当 pandas.dataframe.values 切片工作时，从 pandas.dataframe.iloc 切片制作列表不起作用
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Making lists from pandas.dataframe.iloc slice doesn't work while pandas.dataframe.values slice work
提问by Ando Jurai
I want to agregate columns from a dataframe into a new columns
我想将数据框中的列聚合到新列中
So I used:
所以我使用了：
newdataframe["agregate1"]=list(df.iloc[:,0:4])
but it doesn't work. It returns an ["intensity_x"] list (with x as column index), these strings being the names of my dataframe columns.
但它不起作用。它返回一个 ["intensity_x"] 列表（x 作为列索引），这些字符串是我的数据框列的名称。
While
尽管
newdataframe["agregate1"]=list(df.iloc[0,0:4])
will return data such as
将返回数据，如
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 2920000000.0, 2830000000.0, 3030000000.0, 0.0, 2980000000.0, 3000000000.0].
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 2920000000.0, 2830000000.0, 3030000000.0, 0.0, 2980000000.0, 3000000]
It is actually important since I can't retrieve correctly my data and it seems like a bug, or I am missing something important.
这实际上很重要，因为我无法正确检索我的数据，这似乎是一个错误，或者我遗漏了一些重要的东西。
By reading: pack dataframe columns to list in pandas
通过阅读： pack dataframe columns to list in pandas
I circumvented the problem by using df.values instead of iloc, still I don't understand what is the problem with using "whole slices", only getting headers instead. This is strange. Thanks
我通过使用 df.values 而不是 iloc 规避了这个问题，但我仍然不明白使用“整个切片”有什么问题，只得到标题。这很奇怪。谢谢
采纳答案by jezrael
If use:
如果使用：
df1 = df.iloc[:,0:4]
output is DataFrame.
输出是DataFrame。
If:
如果：
df2 = df.iloc[0,0:4]
Output is Series- first rowin dfand columns 1:4.
输出是Series-first rowindf和列1:4。
Sample:
样本：
df = pd.DataFrame({'A':[1,2,3],
'B':[4,5,6],
'C':[7,8,9],
'D':[1,3,5],
'E':[5,3,6],
'F':[7,4,3]})
print (df)
A B C D E F
0 1 4 7 1 5 7
1 2 5 8 3 3 4
2 3 6 9 5 6 3
df1 = df.iloc[:,0:4]
print (df1)
A B C D
0 1 4 7 1
1 2 5 8 3
2 3 6 9 5
df2 = df.iloc[0,0:4]
print (df2)
A 1
B 4
C 7
D 1
Name: 0, dtype: int64
Then you can use valuesif need output as numpy array:
然后你可以使用valuesif 需要输出为numpy array：
print (df1.values)
[[1 4 7 1]
[2 5 8 3]
[3 6 9 5]]
If need output listof lists, use:
如果需要输出list的lists，使用：
print (df1.values.tolist())
[[1, 4, 7, 1], [2, 5, 8, 3], [3, 6, 9, 5]]
If need list in new column:
如果需要在新列中列出：
df['new'] = df.iloc[:,0:4].values.tolist()
print (df)
A B C D E F new
0 1 4 7 1 5 7 [1, 4, 7, 1]
1 2 5 8 3 3 4 [2, 5, 8, 3]
2 3 6 9 5 6 3 [3, 6, 9, 5]
df['new'] = list(df.iloc[:,0:4].values)
print (df)
A B C D E F new
0 1 4 7 1 5 7 [1, 4, 7, 1]
1 2 5 8 3 3 4 [2, 5, 8, 3]
2 3 6 9 5 6 3 [3, 6, 9, 5]
