I have an excel file that has diffrent weather stations and the minimum and maximum temprature of every month in a year like this:

Not quite well versed in Python, but have been trying to follow the pandas user guide and looking at forums using different methods to pivot the table with pandas so the header with the values below becomes like this, but without luck.

This was my final attempt. It results into outputing the header in the wrong order, and the first row of values.

import pandas as pd

df = pd.read_excel('input.xlsx')

result = df.pivot_table(index='Time', columns='Name', values=['Minimum', 'Maximum'])

result.columns = ['_'.join(col) for col in result.columns]

result.to_excel('output.xlsx')

CodePudding user response：

Using a pivot makes sense to me too. Is that where your problems is occurring? Then maybe some of the columns in your example data are part of the index of your input table. The most difficult part is to get all the columns sorted and named as in your expected output. This works for me with some sample data:

import numpy as np
import pandas as pd

# Sample data
df = pd.DataFrame({
    "Name": np.repeat([f"Station {i}" for i in range(1, 5)], 12),
    "Time": np.tile([f"2020-{i:02d}" for i in range(1, 13)], 4),
    "Minimum": np.random.randint(-10, 0, size=48),
    "Maximum": np.random.randint(0, 10, size=48)
})

df = df.pivot(index="Time", columns="Name")
df = df.sort_index(axis=1, level=[1, 0], ascending=[True, False])
df = df.set_axis(df.columns.to_flat_index().map(" - ".join), axis=1)
df = df.reset_index(names="Date")

output:

       Date  Minimum - Station 1  Maximum - Station 1  ...  Maximum - Station 3  Minimum - Station 4  Maximum - Station 4
0   2020-01                   -9                    2  ...                    1                   -4                    5
1   2020-02                   -4                    5  ...                    2                   -9                    5
2   2020-03                   -1                    8  ...                    2                   -7                    0
3   2020-04                   -9                    0  ...                    9                   -7                    7
4   2020-05                   -4                    6  ...                    1                   -4                    9
5   2020-06                   -9                    2  ...                    6                   -2                    5
6   2020-07                   -9                    2  ...                    1                   -5                    5
7   2020-08                   -6                    2  ...                    8                   -6                    0
8   2020-09                   -3                    2  ...                    2                  -10                    0
9   2020-10                   -2                    5  ...                    1                   -2                    4
10  2020-11                  -10                    7  ...                    7                   -2                    5
11  2020-12                   -6                    8  ...                    3                   -2                    8