如何将数据类型的 pandas 数据框更改为定义格式的字符串？ [英] How do I change data-type of pandas data frame to string with a defined format?

问题描述

我开始把我的头发撕掉 - 所以我希望有人可以帮忙。我有一个使用openpyxl从Excel电子表格创建的熊猫DataFrame。生成的DataFrame如下所示：

  print image_name_data 
 id image_name 
 0 1001 1001_mar2014_report 
 1 1002 1002_mar2014_report 
 2 1003 1003_mar2014_report 
 
 [3 rows x 2 columns] 
  

...

  print image_name_data.dtypes 
 id float64 
 image_name object 
 dtype：object 
  

问题在于，id列中的数字实际上是身份证号码，我需要把它们作为字符串。我已经尝试将ID列转换为字符串使用：

$ p $ image_name_data ['id'] = image_name_data ['id']。 astype（'str'）


这看起来有点难看，但确实产生了一个类型为object '而不是'float64'：

  print image_name_data.dyptes 
 id对象
 image_name对象
 dtype：object 
  

但是，创建的字符串有一个小数点，如下所示： p>

  print image_name_data 
 id image_name 
 0 1001.0 1001_mar2014_report 
 1 1002.0 1002_mar2014_report 
 2 1003.0 1003_mar2014_report 
 
 [3行x 2列] 
  

如何转换在一个pandas DataFrame中的float64列转换为一个给定格式的字符串（在这种情况下，例如'％10.0f'）？ 我无法重现你的问题但是你有尝试将它转换为一个整数第一？

image_name_data ['id'] = image_name_data ['id']。astype（int ）.astype（'str'）

然后，关于更一般的问题，可以使用 map （在这个答案）。在你的情况：
image_name_data ['id'] = image_name_data ['id']。map（'{：。0f}'。format）

I'm starting to tear my hair out with this - so I hope someone can help. I have a pandas DataFrame that was created from an Excel spreadsheet using openpyxl. The resulting DataFrame looks like:

print image_name_data
     id           image_name
0  1001  1001_mar2014_report
1  1002  1002_mar2014_report
2  1003  1003_mar2014_report

[3 rows x 2 columns]

…with the following datatypes:

print image_name_data.dtypes
id            float64
image_name     object
dtype: object

The issue is that the numbers in the id column are, in fact, identification numbers and I need to treat them as strings. I've tried converting the id column to strings using:

image_name_data['id'] = image_name_data['id'].astype('str')

This seems a bit ugly but it does produce a variable of type 'object' rather than 'float64':

print image_name_data.dyptes
id            object
image_name    object
dtype: object

However, the strings that are created have a decimal point, as shown:

print image_name_data
       id           image_name
0  1001.0  1001_mar2014_report
1  1002.0  1002_mar2014_report
2  1003.0  1003_mar2014_report

[3 rows x 2 columns]

How can I convert a float64 column in a pandas DataFrame to a string with a given format (in this case, for example, '%10.0f')?

解决方案

I'm unable to reproduce your problem but have you tried converting it to an integer first?

image_name_data['id'] = image_name_data['id'].astype(int).astype('str')

Then, regarding your more general question you could use map (as in this answer). In your case: image_name_data['id'] = image_name_data['id'].map('{:.0f}'.format)

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