Using Pandas to calculate the percentage of each index's values
Question:
I get stuck in pandas when I have a DataFrame like this:
Person
Fruit
A
Apple
A
Banana
A
Banana
B
Apple
C
Banana
A
Apple
F
Banana
D
Banana
I need to calculate the percentage of each person’s different fruits, like A has 4 fruits, which will return 50% Apple and 50% Banana. D has 1 fruit, which will return 100% Banana.
Is there any method that I can achieve this result?
Thank you so much for help!
Answers:
You can use pandas.Series.value_counts :
result = (
(df.groupby('Person')['Fruit']
.value_counts(normalize=True))
.astype(float)
.map("{:.2%}".format)
)
# Output :
print(result)
Person Fruit
A Apple 50.00%
Banana 50.00%
B Apple 100.00%
C Banana 100.00%
D Banana 100.00%
F Banana 100.00%
Name: Fruit, dtype: object
I get stuck in pandas when I have a DataFrame like this:
| Person | Fruit |
|---|---|
| A | Apple |
| A | Banana |
| A | Banana |
| B | Apple |
| C | Banana |
| A | Apple |
| F | Banana |
| D | Banana |
I need to calculate the percentage of each person’s different fruits, like A has 4 fruits, which will return 50% Apple and 50% Banana. D has 1 fruit, which will return 100% Banana.
Is there any method that I can achieve this result?
Thank you so much for help!
You can use pandas.Series.value_counts :
result = (
(df.groupby('Person')['Fruit']
.value_counts(normalize=True))
.astype(float)
.map("{:.2%}".format)
)
# Output :
print(result)
Person Fruit
A Apple 50.00%
Banana 50.00%
B Apple 100.00%
C Banana 100.00%
D Banana 100.00%
F Banana 100.00%
Name: Fruit, dtype: object