在 Pandas 中，read_excel() 中使用的 read_csv() 中的“nrows”相当于什么？
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In Pandas, whats the equivalent of 'nrows' from read_csv() to be used in read_excel()?
提问by Gabriel
Want to import only certain range of data from an excel spreadsheet (.xlsm format as it has macros) into a pandas dataframe. Was doing it this way:
只想将特定范围的数据从 excel 电子表格（.xlsm 格式，因为它具有宏）导入到 Pandas 数据框中。是这样做的：
data = pd.read_excel(filepath, header=0, skiprows=4, nrows= 20, parse_cols = "A:D")
But it seems that nrows works only with read_csv() ? What would be the equivalent for read_excel()?
但似乎 nrows 仅适用于 read_csv() ？read_excel() 的等价物是什么？
采纳答案by Erol
If you know the number of rows in your Excel sheet, you can use the skip_footerparameter to read the first n - skip_footerrows of your file, where nis the total number of rows.
如果您知道 Excel 工作表中的行数，则可以使用skip_footer参数读取文件的前n - skip_footer行，其中n是总行数。
http://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_excel.html
http://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_excel.html
Usage:
用法：
data = pd.read_excel(filepath, header=0, parse_cols = "A:D", skip_footer=80)
Assuming your excel sheet has 100 rows, this line would parse the first 20 rows.
假设您的 Excel 表有 100 行，该行将解析前 20 行。
回答by MaxU
I'd like to make (extend) @Erol's answerbit more flexible.
我想让（扩展）@Erol 的回答更灵活一些。
Assuming that we DON'T know the total number of rows in the excel sheet:
假设我们不知道excel表中的总行数：
xl = pd.ExcelFile(filepath)
# parsing first (index: 0) sheet
total_rows = xl.book.sheet_by_index(0).nrows
skiprows = 4
nrows = 20
# calc number of footer rows
# (-1) - for the header row
skipfooter = total_rows - nrows - skiprows - 1
df = xl.parse(0, skiprows=skiprows, skipfooter=skipfooter, parse_cols="A:D") \
.dropna(axis=1, how='all')
.dropna(axis=1, how='all')will drop all columns containing onlyNaN's
.dropna(axis=1, how='all')将删除所有只包含NaN's 的列
回答by NathanielDavidChu
As noted in the documentation, as of pandas version 0.23, this is now a built-in option, and functions almost exactly as the OP stated.
正如文档中所述，从 pandas 版本 0.23 开始，这现在是一个内置选项，其功能几乎与 OP 所述完全相同。
The code
编码
data = pd.read_excel(filepath, header=0, skiprows=4, nrows= 20, use_cols = "A:D")
data = pd.read_excel(filepath, header=0, skiprows=4, nrows= 20, use_cols = "A:D")
will now read the excel file, take data from the first sheet (default), skip 4 rows of data, thentake the first line (i.e., the fifth line of the sheet) as the header, read the next 20 rows of data into the dataframe (lines 6-25), and only use the columns A:D. Note that use_cols is now the final option, as parse_cols is deprecated.
现在将读取excel文件，从第一张工作表中取数据（默认），跳过4行数据，然后以第一行（即工作表的第五行）为标题，将接下来的20行数据读入数据框（第 6-25 行），并且仅使用 A:D 列。请注意， use_cols 现在是最后一个选项，因为 parse_cols 已被弃用。
