[英]How to create a list of lists where the sub-lists are the column values for each column
I'm a newbie in python and pandas. 我是蟒蛇和熊猫的新手。 I'm trying to put all rows with one column into each index of the list.
我正在尝试将包含一列的所有行放入列表的每个索引中。
Here is my code. 这是我的代码。
result = pd.concat(result, axis=1).fillna(method='bfill').fillna(method='ffill')
the ouput of print is like 印刷的输出就像
1 2
0 0.57 739.679993
1 0.57 739.679993
2 0.57 739.679993
3 0.57 739.679993
4 0.57 739.679993
5 0.57 739.679993
6 0.57 739.679993
7 0.57 739.679993
8 0.57 739.679993
9 0.57 739.679993
10 0.57 739.679993
11 0.57 739.679993
12 0.57 739.679993
13 0.57 739.679993
14 0.57 739.679993
15 0.57 739.679993
16 0.57 739.679993
17 0.57 739.679993
18 0.57 739.679993
19 0.57 739.679993
20 0.57 739.679993
21 0.57 739.679993
22 0.57 739.679993
23 0.57 739.679993
24 0.57 739.679993
25 0.57 739.679993
26 0.57 739.679993
27 0.57 739.679993
28 0.57 739.679993
29 0.57 739.679993
... ... ...
121571 0.72 738.000000
121572 0.72 738.000000
121573 0.72 738.000000
121574 0.72 738.000000
121575 0.72 738.000000
121576 0.72 738.000000
121577 0.72 738.000000
121578 0.72 738.000000
121579 0.72 738.000000
121580 0.72 738.000000
121581 0.72 738.000000
121582 0.72 738.000000
121583 0.72 738.000000
121584 0.72 738.000000
121585 0.72 738.000000
121586 0.72 738.000000
121587 0.72 738.000000
121588 0.72 738.000000
121589 0.72 738.000000
121590 0.72 738.000000
121591 0.72 738.000000
121592 0.72 738.000000
121593 0.72 738.000000
121594 0.72 738.000000
121595 0.72 738.000000
121596 0.72 738.000000
121597 0.72 738.000000
121598 0.72 738.000000
121599 0.72 738.000000
121600 0.72 738.000000
I want to put whole rows with each column to the list. 我想将每列的整行放到列表中。 For example, there is a list
result_temp = []
例如,有一个列表
result_temp = []
for i in range(0, lenghofColumn):
result_temp.append(result[:,i])
However, it gives me an error that says Error: TypeError: unhashable type
但是,它给出了一个错误:
Error: TypeError: unhashable type
File "public/make_bokeh.py", line 49, in <module>
real_result.append(result_temp[:,i])
Is there any ways to do it...? 有没有办法做到这一点......?
Please help me out here... 请帮帮我...
Thanks in advance. 提前致谢。
The best is transpose values, convert to numpy array
and last to list
s: 最好的是转置值,转换为
numpy array
,最后是list
s:
result_temp = result.T.values.tolist()
I think you can use list comprehension
where loop by columns names and select each column by name by []
and convert to list
: 我认为您可以使用
list comprehension
,其中按列名称循环,并按[]
按名称选择每列,并转换为list
:
result_temp = [result[x].tolist() for x in result.columns]
it is same as: 它与:
result_temp = []
for x in result.columns:
result_temp.append(result[x].tolist())
If want use your code need DataFrame.iloc
for select column by position: 如果想要使用你的代码需要
DataFrame.iloc
来按位置选择列:
result_temp = []
lenghofColumn = len(result.columns)
for i in range(0, lenghofColumn):
result_temp.append(result.iloc[:,i].tolist())
print (result_temp)
It is same as: 它与:
result_temp = [result.iloc[:,i].tolist() for i in range(0, lenghofColumn)]
Couple of other alternatives 几个其他替代品
Alt 1 替代1
When using df
in a list
context, you'll get each column name 在
list
上下文中使用df
时,您将获得每个列名称
[list(result[c]) for c in result]
Alt 2 替代2
Fun with map
有趣的
map
list(map(list, map(result.get, result)))
Alt 3 替代3
zip
transpose with tuple
s 带有
tuple
的zip
转置
list(zip(*result.values))
With list
s 随着
list
list(map(list, zip(*result.values)))
Alt 4 替代4
list(df.to_dict('list').values())
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