Pandas - 旋转和重新排列 Table 多个标签相同 Header
Pandas - Pivot and Rearrange Table With Multiple Labels in Same Header
我有一个 xlsx 文件,其中包含多年数据的选项卡。每个选项卡都包含一个包含许多列的 table,table 的结构如下:
+-----------+-------+-------------------------+----------------------+
| City | State | Number of Drivers, 2019 | Number of Cars, 2019 |
+-----------+-------+-------------------------+----------------------+
| LA | CA | 123 | 10.0 |
| San Diego | CA | 456 | 2345 |
+-----------+-------+-------------------------+----------------------+
我想将 table 重新排列成这样,并为 xlsx 中的每个选项卡执行此操作:
+-----------+-------+------+-------------------+---------------+
| City | State | Year | Measure Name | Measure Value |
+-----------+-------+------+-------------------+---------------+
| LA | CA | 2019 | Number of Drivers | 123 |
| San Diego | CA | 2019 | Number of Drivers | 456 |
| LA | CA | 2019 | Number of Cars | 10 |
| San Diego | CA | 2019 | Number of Cars | 2345 |
+-----------+-------+------+-------------------+---------------+
这其中有很多变动的部分,要使最终的格式正确也有点棘手。
我们做 melt
然后 join
和 str.split
s=df.melt(['City','State'])
s=s.join(s.variable.str.split(',',expand=True))
Out[120]:
City State variable value 0 1
0 LA CA NumberofDrivers,2019 123.0 NumberofDrivers 2019
1 SanDiego CA NumberofDrivers,2019 456.0 NumberofDrivers 2019
2 LA CA NumberofCars,2019 10.0 NumberofCars 2019
3 SanDiego CA NumberofCars,2019 2345.0 NumberofCars 2019
# if you need change the name adding .rename(columns={}) at the end
这就是我如何将 Yoben 的解决方案应用于 xlsx 文件中的每个选项卡,将它们附加在一起并将完整的 table 写入 .csv:
sheets_dict = pd.read_excel(r'file.xlsx', sheet_name=None)
full_table = pd.DataFrame()
for name, sheet in sheets_dict.items():
sheet['sheet'] = name
sheet = sheet.melt(['City','State'])
sheet = sheet.join(sheet.variable.str.split(',' , expand=True))
full_table = full_table.append(sheet)
full_table.reset_index(inplace=True, drop=True)
full_table.to_csv('Full Table.csv')
我有一个 xlsx 文件,其中包含多年数据的选项卡。每个选项卡都包含一个包含许多列的 table,table 的结构如下:
+-----------+-------+-------------------------+----------------------+
| City | State | Number of Drivers, 2019 | Number of Cars, 2019 |
+-----------+-------+-------------------------+----------------------+
| LA | CA | 123 | 10.0 |
| San Diego | CA | 456 | 2345 |
+-----------+-------+-------------------------+----------------------+
我想将 table 重新排列成这样,并为 xlsx 中的每个选项卡执行此操作:
+-----------+-------+------+-------------------+---------------+
| City | State | Year | Measure Name | Measure Value |
+-----------+-------+------+-------------------+---------------+
| LA | CA | 2019 | Number of Drivers | 123 |
| San Diego | CA | 2019 | Number of Drivers | 456 |
| LA | CA | 2019 | Number of Cars | 10 |
| San Diego | CA | 2019 | Number of Cars | 2345 |
+-----------+-------+------+-------------------+---------------+
这其中有很多变动的部分,要使最终的格式正确也有点棘手。
我们做 melt
然后 join
和 str.split
s=df.melt(['City','State'])
s=s.join(s.variable.str.split(',',expand=True))
Out[120]:
City State variable value 0 1
0 LA CA NumberofDrivers,2019 123.0 NumberofDrivers 2019
1 SanDiego CA NumberofDrivers,2019 456.0 NumberofDrivers 2019
2 LA CA NumberofCars,2019 10.0 NumberofCars 2019
3 SanDiego CA NumberofCars,2019 2345.0 NumberofCars 2019
# if you need change the name adding .rename(columns={}) at the end
这就是我如何将 Yoben 的解决方案应用于 xlsx 文件中的每个选项卡,将它们附加在一起并将完整的 table 写入 .csv:
sheets_dict = pd.read_excel(r'file.xlsx', sheet_name=None)
full_table = pd.DataFrame()
for name, sheet in sheets_dict.items():
sheet['sheet'] = name
sheet = sheet.melt(['City','State'])
sheet = sheet.join(sheet.variable.str.split(',' , expand=True))
full_table = full_table.append(sheet)
full_table.reset_index(inplace=True, drop=True)
full_table.to_csv('Full Table.csv')