按整数索引 pandas 数据帧 [英] Indexing a pandas dataframe by integer

问题描述

我似乎找不到一种优雅的方式来索引 pandas.DataFrame整数索引.在以下示例中，我想从 'A' 列的第一个元素中获取值 'a'.

I can't seem to find an elegant way to index a pandas.DataFrame by an integer index. In the following example I want to get the value 'a' from the first element of the 'A' column.

import pandas
df = pandas.DataFrame(
    {'A':['a','b', 'c'], 'B':['f', 'g', 'h']}, 
    index=[10,20,30]
    )

我希望 df['A'].ix[0] 和 df['A'][10] 都返回 'a'.df['A'][10] 确实返回 'a'，但是 df['A'].ix[0] 抛出KeyError: 0.我能想到的根据索引 0 获取值 'a' 的唯一方法是使用以下方法.

I would expect df['A'].ix[0] and df['A'][10] both to return 'a'. The df['A'][10] does return 'a', but df['A'].ix[0] throws a KeyError: 0. The only way I could think of to get the value 'a' based on the index 0 is to use the following approach.

df['A'][df['A'].index[0]]

是否有更短的方法可以使用 0 索引从数据帧中获取 'a' ?

Is there a shorter way to get 'a' out of the dataframe, using the 0 index?

更新

从 pandas 0.11 开始，还有另一种方法可以索引按整数.

As of pandas 0.11 there is a another way to index by integer.

df.iloc[0] # integer based, gives the first row
df.loc[10] # label based, gives the row with label 10

这个取代irow方法.

推荐答案

df['A'].ix[0] 出现错误，因为您的索引不是从 0 开始的，它从 10 开始.您可以通过以下任一方式获得您想要的值

You get an error with df['A'].ix[0] because your indexing doesn't start at 0, it starts at 10. You can get the value you want with either of the following

df['A'].ix[10]
df['A'].irow(0)

第一个使用正确的索引.第二个命令，我怀疑是你想要的，通过行号而不是索引值找到值，技术上只比 if df['A'].ix[0]<长两个字符/code> 工作.

The first uses by the correct index. The second command, which I suspect is what you want, finds the value by the row number, rather than by index value, and is technically only two characters longer than if df['A'].ix[0] worked.

或者，您可以重置索引，以便它们以您期望的方式响应 df['A'].ix[0]:

Alternatively, you can reset the indices so that they will respond the way you expect for df['A'].ix[0]:

df2=df.reset_index()

这将通过将旧索引(10、20 等)移动到 df2 数据框中名为index"的列中来保留它们.然后 df2['A'].ix[0] 将返回 'a'.如果要删除旧的基于 10 的索引，可以在 reset_index 函数的括号中插入标志 drop=True.

This will preserve your old indices (10, 20, etc.) by moving them into a column called "index" in the df2 data frame. Then df2['A'].ix[0] will return 'a'. If you want to remove the old 10-based indices, you can insert the flag drop=True into the parenthesis of the reset_index function.

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