如何使用panda从文件中提取html表

Question

我是熊猫的新手，我正在尝试从一些HTML文件中提取一些数据。

如何转换多个HTML表，如下所示：

PS4
Game Name | Price
GoW       | 49.99
FF VII R  | 59.99
XBX
Game Name | Price
Gears 5   | 49.99
Forza 5   | 59.99

<table>
<tr colspan="2">
<td>PS4</td>
</tr>
<tr>
<td>Game Name</td>
<td>Price</td>
</tr>
<tr>
<td>GoW</td>
<td>49.99</td>
</tr>
<tr>
<td>FF VII R</td>
<td>59.99</td>
</tr>
</table>
<table>
<tr colspan="2">
<td>XBX</td>
</tr>
<tr>
<td>Game Name</td>
<td>Price</td>
</tr>
<tr>
<td>Gears 5</td>
<td>49.99</td>
</tr>
<tr>
<td>Forza 5</td>
<td>59.99</td>
</tr>
</table>

转换成如下json对象：

[
{ "Game Name": "Gow", "Price": "49.99", "platform": "PS4"},
{ "Game Name": "FF VII R", "Price": "59.99", "platform": "PS4"},
{ "Game Name": "Gears 5", "Price": "49.99", "platform": "XBX"},
{ "Game Name": "Forza 5", "Price": "59.99", "platform": "XBX"}
]

我试图用pandas.read_html(path/to/file(加载包含表的html文件，它确实返回了一个DataFrames列表，但我不知道如何提取之后的数据，尤其是平台名称在标题中，而不是作为一个单独的列。

我使用panda是因为我从本地htm文件中提取这些表，这些文件包含其他形式的表和HTML代码，所以我使用：

tables = pandas.read_html(file_path, match="Game Name")

以便使用基于该列名的match参数快速隔离我需要的表。

Answer 1

import pandas as pd
# list to save all dataframe from all tables in all files
df_list = list()
# list of files to load
list_of_files = ['test.html']
# iterate through your files
for file in list_of_files:

# create a list of dataframes from the tables in the file
dfl = pd.read_html(file, match='Game Name')

# fix the headers and columns
for d in dfl:
# select row 1 as the headers
d.columns = d.iloc[1]
# select row 0, column 0 as the platform
d['platform'] = d.iloc[0, 0]
# selection row 2 and below as the data, row 0 and 1 were the headers
d = d.iloc[2:]
# append the cleaned dataframe to df_list
df_list.append(d.copy())

# create a single dataframe
df = pd.concat(df_list).reset_index(drop=True)
# create a list of dicts from df
records = df.to_dict('records')
print(records)
[out]:
[{'Game Name': 'GoW', 'Price': '49.99', 'platform': 'PS4'},
{'Game Name': 'FF VII R', 'Price': '59.99', 'platform': 'PS4'},
{'Game Name': 'Gears 5', 'Price': '49.99', 'platform': 'XBX'},
{'Game Name': 'Forza 5', 'Price': '59.99', 'platform': 'XBX'}]