pandas read_html返回值处理方法
*
– 0、前言
–
+ 0.2 read_html
– 1、表格设计
– 2、代码部分
– 3、执行结果
– 4、结果分析
–
+ 4.1 什么情况下返回值是List，什么时候是DataFrame
+ 4.2 如何把List转换为DataFrame
+ 4.3 如何打印表格及如何保存到Excel表格
+ 4.4 如何行索引
+ 4.5 如何列索引
+ 4.6 如何行列索引
– 5、pandas dataframe 方法示例
–
+ 5.1 pandas dropna()移除空行、空列
+ 5.2 pandas drop() 删除列
+ 5.3 pandas drop() 删除行
+ 5.4 DataFrame数据格式化 (设置小数位数)
+ 5.5 DataFrame数据格式化 (设置百分比)
+ 5.6 DataFrame数据格式化 (设置千分位分隔符)
0、前言
0.1 认识DataFrame
Pandas DataFrame入门教程（图解版）
Pandas 数据结构 – DataFrame
; 0.2 read_html
pandas.read_html(io,
match='.+',
flavor=None,
header=None,
index_col=None,
skiprows=None,
attrs=None,
parse_dates=False,
tupleize_cols=None,
thousands=', ',
encoding=None,
decimal='.',
converters=None,
na_values=None,
keep_default_na=True,
displayed_only=True)
1、表格设计
'''
表格设计如下
ID Options Description Value
MTODORULE1 SWPERMIT Allow Software use True
MTODORULE2 NaN NaN NaN
MTODORULE3 NaN NaN NaN
'''
2、代码部分
import pandas as pd
url = 'https://docs.qq.com/doc/xxx'
data = pd.read_html(url, header=0,encoding='utf-8')
data0 = pd.read_html(url, header=0,encoding='utf-8')[0]
print('-------------------------------------------------')
print(type(data))
print(data)
print('-------------------------------------------------')
print(type(data0))
print(data0)
print('-------------------------------------------------')
df = data[0]
print(type(df))
print(df)
print('-------------------------------------------------')
print(df['Value'])
print('-------------------------------------------------')
print(df.loc[0])
print('-------------------------------------------------')
print(df['Value'].loc[0])
print(df['ID'].loc[0])
print('-------------------------------------------------')
3、执行结果
`python
ID Options Description Value
0 MTODORULE1 SWPERMIT Allow Software use True
1 MTODORULE2 NaN NaN NaN
2 MTODORULE3 NaN NaN NaN
0 True
1 NaN
2 NaN
Name: Value, dtype: object
True
MTODORULE1
Original: https://blog.csdn.net/qq_33704787/article/details/124650016
Author: CDamogu
Title: Python pandas read_html返回值List，DataFrame索引方法（行，列索引，行列索引）示例 | dataframe移除空行列、移除行列、数据格式化小数位、百分比、千分位分隔
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