在 pandas 中迭代生成列名 [英] generating column names iteratively in pandas

问题描述

我有一个11列的Pandas DataFrame，df

I have an 11 column Pandas DataFrame, df

Name aaa bbb ccc ddd eee fff ggg hhh iii jjj kkk

我想重命名列，以便新标题为

I want to rename the columns so that the new header is

Name type_1 type_2 type_3 type_4 type_5 expt_1 expt_2 expt_3 expt_4 expt_5

我可以使用df.rename，但必须手动输入新名称.

I can use df.rename but I will have to manually type in the new names.

您能告诉我如何将名称迭代地更改为type_*或expt_*吗?

Can you tell me how I can change the names iteratively to type_* or expt_*? where

* = half the number of columns excluding the first one (Name)

之所以问这个问题，是因为我想将这个命名系统推广到一个具有1000列的大表中.

I ask this because I want to generalize this naming system to a large table with 1000 columns.

推荐答案

编辑:这将更适合于任意数量的列(偶数或奇数)

this will be better suited to an arbitrary number of columns (either even or odd in number)

# get length of df's columns
num_cols = len(list(df))

# generate range of ints for suffixes
# with length exactly half that of num_cols;
# if num_cols is even, truncate concatenated list later
# to get to original list length
rng = range(1, (num_cols / 2) + 1)

new_cols = ['Name'] + ['type_' + str(i) for i in rng] + ['expt_' + str(i) for i in rng]

# ensure the length of the new columns list is equal to the length of df's columns
df.columns = new_cols[:num_cols]

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