Negative indexing/selecting working and not working

[deanhystad]

You should start with 1 question.

import pandas as pd

df = pd.DataFrame(
    [
        {"type": "Strongly disagree", "value": 24},
        {"type": "Disagree", "value": 294},
        {"type": "Neither agree nor disagree", "value": 594},
        {"type": "Agree", "value": 1927},
        {"type": "Strongly agree", "value": 376},
    ]
)

df["type_code"] = df.type.map(
    {
        "Strongly disagree": -2,
        "Disagree": -1,
        "Neither agree nor disagree": 0,
        "Agree": 1,
        "Strongly agree": 2,
    }
)

df = df.set_index("type_code").sort_index()

perc = (df["value"] / df["value"].sum()) * 100
df["percentage"] = perc

perc = df["percentage"]
df["percentage_end"] = perc.cumsum() - (perc[-2] + perc[-1] + perc[0] / 2)

perc = df["percentage"]
df["percentage_start"] = df["percentage_end"] - perc

df = df.reset_index(drop=True)

print(df)

Output:
                         type  value  percentage  percentage_end  percentage_start
0           Strongly disagree     24    0.746501      -18.382582        -19.129082
1                    Disagree    294    9.144635       -9.237947        -18.382582
2  Neither agree nor disagree    594   18.475894        9.237947         -9.237947
3                       Agree   1927   59.937792       69.175739          9.237947
4              Strongly agree    376   11.695179       80.870918         69.175739

Grouping and using the apply function on groups is fairly advanced pandas. Save that for later.