将特定列从浮点数转换为小数 [英] Convert specific columns from float to Decimal

问题描述

我有一个数据框，我需要将特定的列范围从浮点数转换为小数(并让它们全部保留小数点后 5 位).我很难转换列.有人可以帮助我这样做吗，最好使用 iloc?我在下面有一个示例代码，它说明了我在寻找什么(有生成示例数据的代码).运行此程序时收到以下错误.

I have a dataframe where I need to convert specific column ranges from floats to decimals (and have them all go out 5 decimal places). I am having a difficult time converting the columns. Can someone help me do so, preferably using iloc? I have a sample code below that illustrates what I am looking for (there is code to generate sample data). I receive the following error when I run this.

追溯:

"TypeError: ('不支持从系列到十进制的转换','发生在索引 B')"

"TypeError: ('conversion from Series to Decimal is not supported', 'occurred at index B')"

import pandas as pd 
from pandas import util
import numpy as np
from decimal import Decimal

df= util.testing.makeDataFrame()
df.head()       
df.iloc[:, 1:4].apply(Decimal)

推荐答案

apply 在 Dataframe 上应用一个函数到该数据框的所有 Series 列.您必须更进一步，将 Decimal 应用于每个 Series 的各个单元格:

apply on a Dataframe applies a function to all the columns of that dataframe which are Series. You have to go one step further and apply Decimal to the individual cells of each Series:

df.iloc[:, 1:4] = df.iloc[:, 1:4].apply(lambda x: x.apply(Decimal))

如果你想量化十进制，只需使用另一个lambda:

If you want to quantize the Decimal, just use another lambda:

df.iloc[:, 1:4] = df.iloc[:, 1:4].apply(lambda x: x.apply(
    lambda y: Decimal(y).quantize(Decimal('1.00000'))))

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