python for loop with if condition

Question

This is my data set:

    q1  q2  q3     q4
0   a   a   a   a
1   b   a   a   a
2   c   c   b   a
3   d   d   b   a
4   a   a   a   a
5   b   c   b   a
6   b   a   b   a
7   c   c   b   a
8   d   d   b   a

where column

q1 has 'a','b','c','d' column values.
q2 has 'a','c','d' column values.
q3 has 'a','b' column values.
q4 has 'a' column values.

I want to run a for-loop for all columns with the common equation, but all the columns do not have all values. I am getting an error.

Example: enter image description here

col = ['q1', 'q2', 'q3', 'q4']

for i in col:
    print((df[i].value_counts()['a']) + (df[i].value_counts()['b']) + (df[i].value_counts()['c']) + (df[i].value_counts()['d']))

can you add the expected output?

biyazelnut
– biyazelnut

2023-02-17 09:26:27 +00:00
Commented Feb 17, 2023 at 9:26 — biyazelnut
– biyazelnut, Commented Feb 17, 2023 at 9:26

NIKUNJ KOTHIYA · Accepted Answer · 2023-02-17 09:28:18Z

1

You can try with multiple if conditions to check the value in the particular column:

col = ['q1', 'q2', 'q3', 'q4']

for i in col:
    count = 0
    if 'a' in df[i].unique():
        count += df[i].value_counts()['a']
    if 'b' in df[i].unique():
        count += df[i].value_counts()['b']
    if 'c' in df[i].unique():
        count += df[i].value_counts()['c']
    if 'd' in df[i].unique():
        count += df[i].value_counts()['d']
    print(count)

answered Feb 17, 2023 at 9:28

NIKUNJ KOTHIYA

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Comments

Louis · Accepted Answer · 2023-02-17 09:51:04Z

0

You can try by declaring the values in your for():

col = ['q1', 'q2', 'q3', 'q4']
values = ['a', 'b', 'c', 'd']
for i in col:
    count = 0
    for v in values:
        if v in df[i].values:
            count += df[i].value_counts()[v]
    print(count)

answered Feb 17, 2023 at 9:51

Louis

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Comments

Tornike Kharitonishvili · Accepted Answer · 2023-02-17 10:05:25Z

0

you can use, create list and append:

list_C = []
for i in cols:
    a = df[i].str.count("A").sum()
    list_C.append(a)
    b = df[i].str.count("B").sum()
    list_C.append(b)
    c = df[i].str.count("C").sum()
    list_C.append(c)
    d = df[i].str.count("D").sum()
    list_C.append(d)

print(list_C)
print(sum(list_C))

answered Feb 17, 2023 at 10:05

Tornike Kharitonishvili

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