pandas根据数据类型筛选数据

Posted 2021-05-18 Data+Science+Insight

pandas根据数据类型筛选数据

 

pandas根据数据类型筛选对应的特征列，因为不同的数据类型列往往对应不同的后续特征处理方法。

select_dtypes是我们使用的主要函数，其中包含两个核心参数，include和exclude

我们将学习如何使用Pandas根据它们的数据类型选择列。例如，如果我们有多个数据类型的Pandas dataframe，

比如数值型和对象型，我们将学习如何选择数值型列，单独进行分析或者特征工程处理。

 

Syntax: DataFrame.select_dtypes(include=None, exclude=None)
Parameters : 
include, exclude : A selection of dtypes or strings to be included/excluded. At least one of these parameters must be supplied.
Return : The subset of the frame including the dtypes in include and excluding the dtypes in exclude.

 

import pandas as pd
import numpy as np

data = {'产品':['肉类','盐铁','纺织','木材']*2,
        '年份':[1046,1046,1046,1046,1047,1047,1047,1047],
       '诸侯':['秦','齐','楚','燕','赵','魏','韩','西周'],
       '产量':[180,140,300,200,150,60,80,320]}

df=pd.DataFrame(data, columns=['产品','年份','诸侯','产量'])

df

df.dtypes

# df.loc[:, df.dtypes == np.float64].head()
df.loc[:, df.dtypes == np.int64].head()

df.select_dtypes(include='number').head()

df.select_dtypes(include='object').head()

df.select_dtypes(exclude='object').head()

df.select_dtypes('float').head()

无返回内容

df.select_dtypes('int64').head()

integer_columns = df.select_dtypes(include=['int64']).columns
float_columns = df.select_dtypes(include=['float64']).columns
object_columns = df.select_dtypes(include=['object']).columns

 

need_columns = df.select_dtypes(include=['object','int64']).columns
need_columns

df.select_dtypes(include=['number']).head()
df.select_dtypes(include=['integer']).head()
df.select_dtypes(include=['floating']).head()
df.select_dtypes(include=[np.float64,np.int64]).head()

 

for i in df.columns[df.dtypes == 'object']:
    print(i)

 

参考：Select Columns with Specific Data Types in Pandas Dataframe

参考：Select Columns with Specific Data Types in Pandas Dataframe

参考：Selecting Pandas Columns by dtype