数据框上的多个条件 [英] multiple conditions on dataframes

问题描述

我正在尝试编写一个新列'is_good'，如果'value'列中的数据集介于 1到6 之间并且'value2'列位于范围从5到10 ，如果它们都不满足这两个条件，则将它们标记为0

I'm trying to write a new column 'is_good' which is marked 1 if the data sets in 'value' column is between range 1 to 6 and when 'value2' column is in range 5 to 10 if they do not satisfy both condition they are marked 0

我知道你是否这样做，

df['is_good'] = [1 if (x >= 1 and x <= 6) else 0 for x in df['value']]

它将根据值的范围填写1或0，但是在标记1或0时我还将如何考虑value2的范围.

it will fill out 1 or 0 depending on the ranges of value but how would I also consider ranges of value2 when marking 1 or 0.

反正我可以不用numpy来实现吗?

Is there anyway I can achieve this without numpy?

先谢谢您！

推荐答案

我认为需要在

I think need double between and chain conditions by & (bitwise and):

df = pd.DataFrame({'value':range(13),'value2':range(13)})
df['is_good'] =  (df['value'].between(1,6) & df['value2'].between(5,10)).astype(int)

或使用4个条件:

df['is_good'] =  ((df['value'] >= 1) & (df['value'] <= 6) & 
                   (df['value2'] >= 5) & (df['value'] <= 10)).astype(int) 


print (df)
    value  value2  is_good
0       0       0        0
1       1       1        0
2       2       2        0
3       3       3        0
4       4       4        0
5       5       5        1
6       6       6        1
7       7       7        0
8       8       8        0
9       9       9        0
10     10      10        0
11     11      11        0
12     12      12        0

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