如何在Pandas的DataFrame中迭代行？ [英] How to iterate over rows in a DataFrame in Pandas?

问题描述

我有一个来自大熊猫的数据框架：

  import pandas as pd 
 inp = [{'c1' 10，'c2'：100}，{'c1'：11，'c2'：110}，{'c1'：12，'c2'：120}] 
 df = pd.DataFrame（inp）
打印df 
  

输出：

  c1 c2 
 0 10 100 
 1 11 110 
 2 12 120 
  

现在我想迭代上面的框架的行。对于每一行，我想要能够通过列的名称访问其元素（单元格中的值）。所以，例如，我想要这样做：

  for df.rows中的行：
打印行['c1']，行['c2'] 
  

有可能在熊猫？

我发现。但它并没有给我我需要的答案。例如，建议在df.T.iteritems（）中使用：

 日期，行：
  

或

  for df.iterrows（）中的行：
  

但是我不明白 row object is and how I can work with it。

解决方案

iterrows 是一种生成索引和行

 在[18]中：for index，df.iterrows（）中的行：
 ....：print row [' c1']，行['c2'] 
 ....：
 10 100 
 11 110 
 12 120 
  pre> 
I have a DataFrames from pandas:
import pandas as pd
inp = [{'c1':10, 'c2':100}, {'c1':11,'c2':110}, {'c1':12,'c2':120}]
df = pd.DataFrame(inp)
print df
Output:
   c1   c2
0  10  100
1  11  110
2  12  120
Now I want to iterate over the rows of the above frame. For every row I want to be able to access its elements (values in cells) by the name of the columns. So, for example, I would like to have something like that:
for row in df.rows:
   print row['c1'], row['c2']
Is it possible to do that in pandas?

I found similar question. But it does not give me the answer I need. For example, it is suggested there to use:
for date, row in df.T.iteritems():
or
for row in df.iterrows():
But I do not understand what the row object is and how I can work with it.
解决方案
iterrows is a generator which yield both index and row
In [18]: for index, row in df.iterrows():
   ....:     print row['c1'], row['c2']
   ....:     
10 100
11 110
12 120


                        
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