我是 pandas 新手，我正在嘗試從一些 HTML 文件中提取一些數(shù)據(jù)。如何轉(zhuǎn)換多個(gè) HTML 表，如下所示： PS4Game Name | PriceGoW | 49.99FF VII R | 59.99 XBXGame Name | PriceGears 5 | 49.99Forza 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>像這樣的 json 對(duì)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"}]我嘗試使用 pandas.read_html(path/to/file) 加載包含表的 html 文件，它確實(shí)返回了 DataFrame 列表，但我不知道之后如何提取數(shù)據(jù)，特別是平臺(tái)名稱(chēng)位于標(biāo)題而不是作為單獨(dú)的列。我使用 pandas 是因?yàn)槲覐陌渌问降谋砀窈?HTML 代碼的本地 htm 文件中提取這些表格，所以我使用：tables = pandas.read_html(file_path, match="Game Name")使用基于該列名稱(chēng)的匹配參數(shù)快速隔離我需要的表。
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紅顏莎娜
TA貢獻(xiàn)1842條經(jīng)驗(yàn) 獲得超13個(gè)贊
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'}]
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