使用条件在Pandas数据框中生成新列 [英] Using conditional to generate new column in pandas dataframe

问题描述

我有一个熊猫数据框，如下所示:

I have a pandas dataframe that looks like this:

   portion  used
0        1   1.0
1        2   0.3
2        3   0.0
3        4   0.8

我想基于used列创建一个新列，以使df看起来像这样:

I'd like to create a new column based on the used column, so that the df looks like this:

   portion  used    alert
0        1   1.0     Full
1        2   0.3  Partial
2        3   0.0    Empty
3        4   0.8  Partial

• 基于
创建新的alert列
• 如果used是1.0，则alert应该是Full.
• 如果used是0.0，则alert应该是Empty.
• 否则，alert应该为Partial.
• Create a new alert column based on
• If used is 1.0, alert should be Full.
• If used is 0.0, alert should be Empty.
• Otherwise, alert should be Partial.

做到这一点的最佳方法是什么?

What's the best way to do that?

推荐答案

您可以定义一个返回不同状态"Full"，"Partial"，"Empty"等的函数，然后使用df.apply来应用该函数每行.请注意，您必须传递关键字参数axis=1以确保它将参数应用于行.

You can define a function which returns your different states "Full", "Partial", "Empty", etc and then use df.apply to apply the function to each row. Note that you have to pass the keyword argument axis=1 to ensure that it applies the function to rows.

import pandas as pd

def alert(c):
  if c['used'] == 1.0:
    return 'Full'
  elif c['used'] == 0.0:
    return 'Empty'
  elif 0.0 < c['used'] < 1.0:
    return 'Partial'
  else:
    return 'Undefined'

df = pd.DataFrame(data={'portion':[1, 2, 3, 4], 'used':[1.0, 0.3, 0.0, 0.8]})

df['alert'] = df.apply(alert, axis=1)

#    portion  used    alert
# 0        1   1.0     Full
# 1        2   0.3  Partial
# 2        3   0.0    Empty
# 3        4   0.8  Partial

这篇关于使用条件在Pandas数据框中生成新列的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！