python - 如何使用 pandas 库对 python 中的浮点值进行分类

Question

` 导入 Pandas 导入 numpy

#importing the dataset
data=pandas.read_csv('gapminder.csv',low_memory=False)

#setting variables to be worked with to numeric
data['urbanrate']=data['urbanrate'].convert_objects(convert_numeric=True)
data['femaleemployrate']=data['femaleemployrate'].convert_objects(convert_numeric=True)
data['lifeexpectancy']=data['lifeexpectancy'].convert_objects(convert_numeric=True)

print("Count for urbanrate")
chk8=data['urbanrate'].value_counts(sort=False,dropna=False)
print(chk8)

sub1=data[['urbanrate','femaleemployrate','lifeexpectancy']]
print (sub1.head(25))

===========================================================================
def urban (row):
      if (row['urbanrate']<25.0):
          return 1
      if (data[['urbanrate']>=25.0 & data['urbanrate']<75.0]):
         return 2
      if (data['urbanrate']>75.0):
         return 3
sub1['urban']=sub1.apply(lambda row: urban (row),axis=1)
print (sub1.head(25))
============================================================================`

我想对 urbanrate 的所有值进行分类(都是 float ，如 24.56、88.98、77.65)分为 3 个不同的类别(一个是 <25 的值，另一个是 >=25 and <75，最后一个是 >=75)并存储这些值在一个新变量中(比如城市)。我怎样才能做到这一点？我已经给出了我的代码。我执行了它，它给我的错误是:

TypeError: ('cannot compare a dtyped [float64] array with a scalar of type [bool]', 'occurred at index 1'))

请帮帮我

Answer 1

我想你可以使用 pd.cut :

import pandas as pd

df = pd.DataFrame({'urbanrate':[10,20,25,30,40,75,80,100]})
print (df)
   urbanrate
0         10
1         20
2         25
3         30
4         40
5         75
6         80
7        100

bins = [0, 24.999, 74.999, 1000]
group_names = [1,2,3]
df['urban'] = pd.cut(df['urbanrate'], bins, labels=group_names)
print (df)
   urbanrate urban
0         10     1
1         20     1
2         25     2
3         30     2
4         40     2
5         75     3
6         80     3
7        100     3