我有一个循环读取文档中的 Excel 工作表。我想将它们全部存储在一个列表中:
DF_list= list()
for sheet in sheets:
df= pd.read_excel(...)
DF_list = DF_list.append(df)
如果我输入:
[df df df df]
它有效。
抱歉,我有 Matlab 背景,不太习惯 Python,但我喜欢它。 谢谢。
.append()
修改列表并返回 None
。
您在第一个循环中用 DF_list
覆盖 None
,并且追加将在第二个循环中失败。
因此:
DF_list = list()
for sheet in sheets:
DF_list.append(pd.read_excel(...))
或者使用列表理解:
DF_list = [pd.read_excel(...) for sheet in sheets]
试试这个
DF_list= list()
for sheet in sheets:
df = pd.read_excel(...)
DF_list.append(df)
或者对于更紧凑的Python,类似这样的事情可能会做
DF_list=[pd.read_excel(...) for sheet in sheets]
如果您将使用参数
sheet_name=None
:
dfs = pd.read_excel(..., sheet_name=None)
它将返回数据框的字典:
sheet_name : 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
完整解决方案如下:
# (0) Variable containing location of excel file containing many sheets
excelfile_wt_many_sheets = 'C:\this\is\my\location\and\filename.xlsx'
# (1) Initiate empty list to hold all sheet specific dataframes
df_list= []
# (2) create unicode object 'sheets' to hold all sheet names in the excel file
df = pd.ExcelFile(excelfile_wt_many_sheets)
sheets = df.sheet_names
# (3) Iterate over the (2) to read in every sheet in the excel into a dataframe
# and append that dataframe into (1)
for sheet in sheets:
df = pd.read_excel(excelfile_wt_many_sheets, sheet)
df_list.append(df)
实际上不需要定义新的列表来存储一堆数据帧。 pandas.ExcelFile 函数应用于具有多个工作表的 Excel 文件,返回 ExcelFile 对象,该对象是一个可以将一堆数据帧捕获在一起的集合。希望下面的代码有帮助。
import pandas as pd
df = pd.ExcelFile('C:\read_excel_file_with_multiple_sheets.xlsx')
sheet_names_list = df.sheet_names
for sheet in sheet_names_list:
df_to_print = df.parse(sheet_name=sheet)
print(df_to_print)