Using IF function in Pandas dataframe

Question

Ive tried to find the OLDEST FEMALE from csv dataset, but I dont know how. Im pretty new to Python and Pandas. I clearly dont know how to use if function here.

import pandas as pd

df = pd.read_csv("people.csv", usecols=['gender', 'age'])

I tried to use something like this

print(df[df["gender"].isin(["F"])].df.age.max())

or like this

if df[df["gender"].all(["F"])] :
print(df.age.max())

even tried this

print(df.loc[df['gender'] == 'F'].max())

but this was before I found the oldest 'M' is the same age as the oldest 'F'

but still cant figure out how to find the oldest female

EDIT : I have to find the oldest female from imported dataset, not to create one. Thank you.

EDIT 2 : Sorry for bothering, I just found out, that the oldest M in my csv have the same age as the oldest F in my csv. This is embarassing

Adding few rows from your csv would help answer the question better — Manjunath K Mayya
– Manjunath K Mayya, Commented Mar 9, 2022 at 18:26

JB_DataScientist · Accepted Answer · 2022-03-09 17:56:50Z

2

You don't actually need an if statement in this context. See below:

import numpy as np
import pandas as pd

df = pd.DataFrame({'gender': ['M', 'F', 'F','F','M'],
      'age': [99,12,45,98,23]})

# Result
print(df[df['gender'] == 'F']['age'].max())

This should give you what you are looking for. Also, don't forget to indent the next line after an if statement.

answered Mar 9, 2022 at 17:56

JB_DataScientist

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1 Comment

Scott Boston Over a year ago

I recommend against using chained indexing, noted by '][' these two characters in a pandas statement back to back. Instead, do this df.loc[df['gender'] == 'F', 'age'].max()

Manjunath K Mayya · Accepted Answer · 2022-03-09 17:55:43Z

2

You can try this. First group by gender and get max values. Then get the age from it for Females.

import pandas as pd
df = pd.DataFrame([['F',20],['F',30], ['M',20]], columns=['gender', 'age'])

df = df.groupby('gender').max().reset_index()
print(df[df['gender'] == 'F'].iloc[0]['age'])

Output is 30 in this example

answered Mar 9, 2022 at 17:55

Manjunath K Mayya

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1 Comment

Manjunath K Mayya Over a year ago

@helperman200: Since the input data was not provided, I have created a sample data, with the column names as specified in the question. Hence ideally this should work. If you are having issues with this, then please provide sample data from your csv. It would help to answer the question better.

Matthew Borish · Accepted Answer · 2022-03-09 18:03:18Z

2

df = pd.DataFrame({'gender':['F', 'M', 'F', 'M','F', 'M'],'age': [12, 33, 43, 22, 18, 16]})

oldest_female = df.loc[df['gender'] == 'F'].max()

print(oldest_female['age'])

edited Mar 9, 2022 at 18:03

answered Mar 9, 2022 at 17:54

Matthew Borish

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1 Comment

Matthew Borish Over a year ago

Not sure I'm following you. This part selects females only df.loc[df['gender'] == 'F'].

Scott Boston · Accepted Answer · 2022-03-09 18:22:12Z

2

To find the row of the oldest female in the data set you can filter your dataframe to only females, the use idxmax to find the index:

df.loc[df.query('gender == "F"')['age'].idxmax()]

This will return the first row in your dataset with a max age of gender 'F'.

answered Mar 9, 2022 at 18:22

Scott Boston

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