Pandas Excel文件解析参数

Question

我有一些旧代码，在'pandas.ExcelFile.parse'功能：

xls_file = pd.ExcelFile(xls_file_path) 
df = xls_file.parse('16')

使用上述或仅此：

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返回Excel文件中所有列的类似数据帧。唯一的区别是，在最后一种情况下，dataframe比第一种情况下有更多的记录。在

“parse（'16'）”是什么意思？不能从熊猫文献中推断出这一点。在

Answer 1

要按索引加载xls_文件的工作表，请将工作表索引作为int传递给xls_文件.parse(). 请记住，在Python中，第一个工作表的索引为0。在

Answer 2

@DeepSpace已经发布了熊猫文档的链接，我们可以在那里找到以下文本：

Equivalent to read_excel(ExcelFile, ...) See the read_excel docstring for more info on accepted parameters

read_excel() docs：

sheetname : string, int, mixed list of strings/ints, or None, default 0

Strings are used for sheet names, Integers are used in zero-indexed sheet positions. Lists of strings/integers are used to request multiple sheets. Specify None to get all sheets. str|int -> DataFrame is returned. list|None -> Dict of DataFrames is returned, with keys representing sheets. Available Cases

Defaults to 0 -> 1st sheet as a DataFrame

1 -> 2nd sheet as a DataFrame

“Sheet1” -> 1st sheet as a DataFrame

[0,1,”Sheet5”] -> 1st, 2nd & 5th sheet as a dictionary of DataFrames

None -> All sheets as a dictionary of DataFrames

Answer 3

根据函数的签名判断，它是sheetname。在

ExcelFile.parse(sheetname=0, header=0, skiprows=None, skip_footer=0, names=None, 
                index_col=None, parse_cols=None, parse_dates=False, date_parser=None,
                na_values=None, thousands=None, convert_float=True, has_index_names=None,
                converters=None, true_values=None, false_values=None, squeeze=False, **kwds)

https://pandas.pydata.org/pandas-docs/stable/generated/pandas.ExcelFile.parse.html