使用 pandas 阅读时，如何删除csv文件的特定列? [英] How to drop a specific column of csv file while reading it using pandas?

问题描述

使用pandas加载csv时，我需要删除标签为 name 的列.我正在阅读csv，如下所示，并希望在其中添加参数.谢谢.

I need to remove a column with label name at the time of loading a csv using pandas. I am reading csv as follows and want to add parameters inside it to do so. Thanks.

pd.read_csv("sample.csv")

我在阅读csv后知道要这样做:

I know this to do after reading csv:

df.drop('name', axis=1)

推荐答案

如果您事先知道列名，则可以通过设置usecols参数

If you know the column names prior, you can do it by setting usecols parameter

当您知道要使用哪些列

假设您有带有['id','name','last_name']列的csv文件，而您只想['name','last_name'].您可以按照以下步骤进行操作:

Suppose you have csv file with columns ['id','name','last_name'] and you want just ['name','last_name']. You can do it as below:

import pandas as pd
df = pd.read_csv("sample.csv", usecols = ['name','last_name'])

何时需要前N列

如果您不知道列名，但是要从数据框中获取前N列.您可以通过

If you don't know the column names but you want first N columns from dataframe. You can do it by

import pandas as pd
df = pd.read_csv("sample.csv", usecols = [i for i in range(n)])

修改

当您知道要删除的列的名称

# Read column names from file
cols = list(pd.read_csv("sample_data.csv", nrows =1))
print(cols)

# Use list comprehension to remove the unwanted column in **usecol**
df= pd.read_csv("sample_data.csv", usecols =[i for i in cols if i != 'name'])

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