pandas 在使用read_csv时添加小数点 [英] Pandas adding decimal points when using read_csv

问题描述

我正在处理一些csv文件，并使用熊猫将它们转换为数据框.之后，我使用输入来查找要删除的值

I'm working with some csv files and using pandas to turn them into a dataframe. After that, I use an input to find values to delete

我挂在一个小问题上:对于某些列，它在列中的值上添加了".o".它只在带有数字的列中执行此操作，因此我猜它正在以浮点数形式读取该列.如何防止这种情况发生?

I'm hung up on one small issue: for some columns it's adding ".o" to the values in the column. It only does this in columns with numbers, so I'm guessing it's reading the column as a float. How do I prevent this from happening?

真正让我感到困惑的部分是，它只发生在几列中，因此我无法完全弄清楚一种模式.我需要将".0"斩掉，以便重新导入它，并且我认为防止它首先发生是最容易的.

The part that really confuses me is that it only happens in a few columns, so I can't quite figure out a pattern. I need to chop off the ".0" so I can re-import it, and I feel like it would be easiest to prevent it from happening in the first place.

谢谢！

这是我的代码示例:

clientid = int(input('What client ID needs to be deleted?'))

df1 = pd.read_csv('Client.csv')
clientclean = df1.loc[df1['PersonalID'] != clientid]
clientclean.to_csv('Client.csv', index=None)

理想情况下，我希望所有值都与原始csv文件相同，但不要包含用户输入中带有clientid的行.

Ideally, I'd like all of the values to be the same as the original csv file, but without the rows with the clientid from the user input.

真正让我感到困惑的部分是，它只发生在几列中，因此我无法完全弄清楚一种模式.我需要将".0"斩掉，以便重新导入它，并且我认为防止它首先发生是最容易的.

The part that really confuses me is that it only happens in a few columns, so I can't quite figure out a pattern. I need to chop off the ".0" so I can re-import it, and I feel like it would be easiest to prevent it from happening in the first place.

谢谢！

推荐答案

这是数据类型问题.

ALollz的评论将我引向正确的方向.熊猫假设数据类型为float，会加上小数点.

ALollz's comment lead me in the right direction. Pandas was assuming a data type of float, which added the decimal points.

使用read_csv时，我将数据类型指定为对象(来自Akarius的评论)，

I specified the datatype as object (from Akarius's comment) when using read_csv, which resolved the issue.

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