以下代码转换为python可用，代码如下：let 源 = Table.FromColumns({Lines.FromBinary(Web.Contents("https://1x2d.titan007.com/" & "2337054" & ".js"), null, null, 936)}), Column1 = 源{50}[Column1], 拆分文本 = Text.Split(Column1, ";"","), 转换为表 = Table.FromList(拆分文本, Splitter.SplitTextByDelimiter(":"), null, null, ExtraValues.Error), 更改的类型 = Table.TransformColumnTypes(转换为表,{{"Column1", type text}}), 按分隔符拆分列 = Table.SplitColumn(更改的类型, "Column1", Splitter.SplitTextByDelimiter("^", QuoteStyle.Csv), {"Column1.1", "Column1.2"}), 按分隔符拆分列1 = Table.ExpandListColumn(Table.TransformColumns(按分隔符拆分列, {{"Column1.2", Splitter.SplitTextByDelimiter(";", QuoteStyle.Csv), let itemType = (type nullable text) meta [Serialized.Text = true] in type {itemType}}}), "Column1.2"), 更改的类型1 = Table.TransformColumnTypes(按分隔符拆分列1,{{"Column1.1", type text}, {"Column1.2", type text}}), 替换的值 = Table.ReplaceValue(更改的类型1,"var gameDetail=Array(","",Replacer.ReplaceText,{"Column1.1"}), 按分隔符拆分列2 = Table.SplitColumn(替换的值, "Column1.2", Splitter.SplitTextByDelimiter("|", QuoteStyle.Csv), {"Column1.2.1", "Column1.2.2", "Column1.2.3", "Column1.2.4", "Column1.2.5", "Column1.2.6", "Column1.2.7"}), 更改的类型2 = Table.TransformColumnTypes(按分隔符拆分列2,{{"Column1.2.1", type number}, {"Column1.2.2", type number}, {"Column1.2.3", type number}, {"Column1.2.4", type text}, {"Column1.2.5", type number}, {"Column1.2.6", type number}, {"Column1.2.7", type number}}), 重命名的列 = Table.RenameColumns(更改的类型2,{{"Column1.1", "公司ID"}, {"Column1.2.1", "胜"}, {"Column1.2.2", "平"}, {"Column1.2.3", "负"}, {"Column1.2.4", "时间"}, {"Column1.2.5", "凯胜"}, {"Column1.2.6", "凯平"}, {"Column1.2.7", "凯负"}}), 筛选的行 = Table.SelectRows(重命名的列, each [时间] <> null and [时间] <> ""),

以下是将该代码转换为Python的代码：

import pandas as pd

url = "https://1x2d.titan007.com/" + "2337054" + ".js"
data = pd.read_csv(url, encoding='gbk', header=None)

column1 = data.iloc[50, 0]
split_text = column1.split(";\"")
converted_table = pd.DataFrame([x.split(":") for x in split_text])
converted_table.columns = ['Column1.1', 'Column1.2']

split_column = converted_table['Column1.2'].str.split('^', expand=True)
split_column.columns = ['Column1.2.1', 'Column1.2.2']
joined_table = pd.concat([converted_table[['Column1.1']], split_column], axis=1)

split_column2 = joined_table['Column1.2.2'].str.split('|', expand=True)
split_column2.columns = ['Column1.2.2.1', 'Column1.2.2.2', 'Column1.2.2.3', 'Column1.2.2.4', 'Column1.2.2.5', 'Column1.2.2.6', 'Column1.2.2.7']
final_table = pd.concat([joined_table[['Column1.1', 'Column1.2.1']], split_column2], axis=1)

final_table = final_table.rename(columns={"Column1.1": "公司ID", "Column1.2.1": "胜", "Column1.2.2.1": "平", "Column1.2.2.2": "负", "Column1.2.2.4": "时间", "Column1.2.2.5": "凯胜", "Column1.2.2.6": "凯平", "Column1.2.2.7": "凯负"})

filtered_table = final_table.dropna(subset=['时间'])
filtered_table = filtered_table[filtered_table['时间'] != '']

print(filtered_table)

请注意，由于我无法访问您提供的网站，因此我使用了示例数据进行转换。如果数据源不同，则代码需要进行适当的修改。