so-71581296/pandas-dataframe-how-to-calculate-the-difference-by-first-row-and-last-row-and

tmp4.py

import pandas as pd
from convtools import conversion as c

# tmp4.csv
"""
Category,CategoryName,time(s),Power,Vapor
1,A,1625448301,593233.36,3353.92
1,A,1625449552,595156.24,3286.8
1,A,1625450802,593833.36,3855.42
2,B,1625452051,595233.37,3353.95
2,B,1625453301,593535.86,3252.92
2,B,1625454552,593473.36,3364.15
3,C,1625455802,593754.32,3233.92
3,C,1625457052,593153.46,3563.52
3,C,1625458301,593854.56,3334.94
4,D,1625459552,593345.75,3353.36
4,D,1625460802,592313.24,3674.95
4,D,1625460802,592313.24,3673.35
1,A,1625463301,597313.23,3658.46
1,A,1625464552,595913.68,3789.45
"""


df = pd.read_csv("tmp4.csv")
col_to_idx = {column: index for index, column in enumerate(df.columns)}


converter = (
    c.chunk_by(c.item(col_to_idx["Category"]))
    .aggregate(
        {
            "Category": c.ReduceFuncs.First(c.this).item(
                col_to_idx["Category"]
            ),
            "CategoryName": c.ReduceFuncs.First(c.this).item(
                col_to_idx["CategoryName"]
            ),
            "TotalTime(s)": (
                c.ReduceFuncs.Last(c.this).item(col_to_idx["time(s)"])
                - c.ReduceFuncs.First(c.this).item(col_to_idx["time(s)"])
            ),
            "Power": c.ReduceFuncs.Sum(c.item(col_to_idx["Power"])),
            "Vapor": c.ReduceFuncs.Sum(c.item(col_to_idx["Vapor"])),
        }
    )
    .pipe(
        c.group_by(c.item("Category"), c.item("CategoryName")).aggregate(
            {
                "Category": c.item("Category"),
                "CategoryName": c.item("CategoryName"),
                "TotalTime(s)": c.ReduceFuncs.Sum(c.item("TotalTime(s)")),
                "Power": c.ReduceFuncs.Sum(c.item("Power")),
                "Vapor": c.ReduceFuncs.Sum(c.item("Vapor")),
            }
        )
        .sort(key=lambda item: item["Category"])
    )
    .gen_converter()
)

data = converter(df.to_records(index=False))

# if you need to get back to a dataframe
df = pd.DataFrame.from_records(data)

"""
   Category CategoryName  TotalTime(s)       Power     Vapor
0         1            A          3752  2975449.87  17944.05
1         2            B          2501  1782242.59   9971.02
2         3            C          2499  1780762.34  10132.38
3         4            D          1250  1777972.23  10701.66
"""

How do I define a sort function to sort the data by category

hi @blockhunts
I've updated the gist, please see above

I see, that's why my code didn't work. I didn't include which column index to be used as the sorting parameter.
Thank you very much for the help.
I hope this library will be bigger and spread further in the community 🥂

I'm glad to help! Thank you for your kind words! :)