Python 从现有数据框的某些列创建新的熊猫数据框
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Creating new pandas dataframe from certain columns of existing dataframe
提问by Sjoseph
I have read loaded a csv file into a pandas dataframe and want to do some simple manipulations on the dataframe. I can not figure out how to create a new dataframe based on selected columns from my original dataframe. My attempt:
我已将 csv 文件读取到 Pandas 数据帧中，并希望对数据帧进行一些简单的操作。我不知道如何根据原始数据框中的选定列创建新的数据框。我的尝试：
names = ['A','B','C','D']
dataset = pandas.read_csv('file.csv', names=names)
new_dataset = dataset['A','D']
I would like to create a new dataframe with the columns A and D from the original dataframe.
我想用原始数据帧中的 A 列和 D 列创建一个新数据帧。
采纳答案by jezrael
It is called subset- passed list of columns in []:
它被称为subset- 传递的列列表[]：
dataset = pandas.read_csv('file.csv', names=names)
new_dataset = dataset[['A','D']]
what is same as:
什么是相同的：
new_dataset = dataset.loc[:, ['A','D']]
If need only filtered output add parameter usecolsto read_csv:
如果只需要过滤输出添加参数usecols到read_csv：
new_dataset = pandas.read_csv('file.csv', names=names, usecols=['A','D'])
EDIT:
编辑：
If use only:
如果仅使用：
new_dataset = dataset[['A','D']]
and use some data manipulation, obviously get:
并使用一些数据操作，显然得到：
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
试图在来自 DataFrame 的切片副本上设置值。
尝试使用 .loc[row_indexer,col_indexer] = value 代替
If you modify values in new_datasetlater you will find that the modifications do not propagate back to the original data (dataset), and that Pandas does warning.
如果new_dataset稍后修改值，您会发现修改不会传播回原始数据 ( dataset)，并且 Pandas 会发出警告。
As pointed EdChumadd copyfor remove warning:
new_dataset = dataset[['A','D']].copy()
