使用条件在 pandas 数据框中生成新列
问题描述
我有一个看起来像这样的熊猫数据框:
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,以便 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
- 根据 创建一个新的
- 如果
used
是1.0
,alert
应该是Full
. - 如果
used
为0.0
,则alert
应为Empty
. - 否则,
alert
应该是Partial
. - Create a new
alert
column based on - If
used
is1.0
,alert
should beFull
. - If
used
is0.0
,alert
should beEmpty
. - Otherwise,
alert
should bePartial
.
alert
列
最好的方法是什么?
解决方案
你可以定义一个函数来返回你的不同状态Full"、Partial"、Empty"等,然后使用 df.apply
将函数应用于每一行.请注意,您必须传递关键字参数 axis=1
以确保它将函数应用于行.
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(row):
if row['used'] == 1.0:
return 'Full'
elif row['used'] == 0.0:
return 'Empty'
elif 0.0 < row['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
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