上一期中,我们重点介绍了pandas中read_excel()中的index_col参数,本期介绍一下usecols参数。官方文档说明:(支持int,str,以及他们的列表,还支持函数调用,默认None解读所有列)usecols : int, str, list-like, or callable default NoneReturn a subset of the columns.
* If None, then parse all columns.
* If int, then indicates last column to be parsed.
.. deprecated:: 0.24.0
Pass in a list of int instead from 0 to `usecols` inclusive.
* If str, then indicates comma separated list of Excel column letters
and column ranges (e.g. "A:E" or "A,C,E:F"). Ranges are inclusive of
both sides.
* If list of int, then indicates list of column numbers to be parsed.
* If list of string, then indicates list of column names to be parsed.
.. versionadded:: 0.24.0
* If callable, then evaluate each column name against it and parse the
column if the callable returns ``True``.
.. versionadded:: 0.24.0
2、代码解释有如下excel表格
# usecols=None也即默认值,默认会解读所有列
>>> df = pd.read_excel(r'D:/myExcel/1.xlsx', sheet_name='Sheet1',usecols=None)>>> df
name math Chinese
0 bob 23 12
1 millor 32 32
2 jiken 61 89
3 tom 34 94
4 json 83 12
5 dela 96 67
6 rison 90 34
# 当usecols指定[0,1]时则仅parse name列以及math列
>>> df = pd.read_excel(r'D:/myExcel/1.xlsx', sheet_name='Sheet1',usecols=[0,1])>>> df
name math
0 bob 23
1 millor 32
2 jiken 61
3 tom 34
4 json 83
5 dela 96
6 rison 90
# 当指定列名时,则仅parse指定的列名列
>>> df = pd.read_excel(r'D:/myExcel/1.xlsx', sheet_name='Sheet1',usecols=['name','Chinese'])>>> df
name Chinese
0 bob 12
1 millor 32
2 jiken 89
3 tom 94
4 json 12
5 dela 67
6 rison 34
# 当然,usecols还接受一个函数,该函数要求,仅有一个入参,# 要求返回结果必须为#boolen类型,如果为True便会解读该列# 定义一个函数,如果列名中包含'm'字符,则返回true
>>> def selectcols(col_name):
return 'm' in col_name
>>> df = pd.read_excel(r'D:/myExcel/1.xlsx', sheet_name='Sheet1',usecols=selectcols)>>> df
name math
0 bob 23
1 millor 32
2 jiken 61
3 tom 34
4 json 83
5 dela 96
6 rison 90
>>>
哈哈,以上就是今天的内容,我相信,一定可以帮助到您。建议平常多调用help()函数,虽然是英文的说明,但真的不难。同时,也要多看看pandas文档,可以关注我的公众号:python小工具。里面有福利哦。