为什么我不能在循环中附加 pandas 数据框 [英] Why can't I append pandas dataframe in a loop

问题描述

我知道有几种方法可以在Pandas中建立数据框.我的问题只是想了解为什么下面的方法不起作用.

I know that there are several ways to build up a dataframe in Pandas. My question is simply to understand why the method below doesn't work.

首先，是一个工作示例.我可以创建一个空的数据框，然后添加一个类似于documenta的新数据框.

First, a working example. I can create an empty dataframe and then append a new one similar to the documenta

In [3]: df1 = pd.DataFrame([[1,2],], columns = ['a', 'b'])
   ...: df2 = pd.DataFrame()    
   ...: df2.append(df1)   

Out[3]: a b 0 1 2

Out[3]: a b 0 1 2

但是，如果执行以下操作，则df2会变为None:

However, if I do the following df2 becomes None:

In [10]: df1 = pd.DataFrame([[1,2],], columns = ['a', 'b'])
    ...: df2 = pd.DataFrame()
    ...: for i in range(10):
    ...:     df2.append(df1)

In [11]: df2
Out[11]:
Empty DataFrame
Columns: []
Index: []

有人可以解释为什么这种方式吗?谢谢！

Can someone explain why it works this way? Thanks!

推荐答案

之所以会发生这种情况，是因为.append()方法返回了新的df:

This happens because the .append() method returns a new df:

熊猫文档(0.19.2):

pandas.DataFrame.append

pandas.DataFrame.append

返回: 已添加: DataFrame

这是一个有效的示例，因此您可以查看循环的每次迭代中发生的情况:

Here's a working example so you can see what's happening in each iteration of the loop:

df1 = pd.DataFrame([[1,2],], columns=['a','b'])
df2 = pd.DataFrame()
for i in range(0,2):
    print(df2.append(df1))

>    a  b
> 0  1  2
>    a  b
> 0  1  2

如果将.append()的输出分配给df(甚至是相同的)，则会得到您可能期望的结果:

If you assign the output of .append() to a df (even the same one) you'll get what you probably expected:

for i in range(0,2):
    df2 = df2.append(df1)
print(df2)

>    a  b
> 0  1  2
> 0  1  2

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