how to remove unwanted zero in the output using pandas

for the below code:

age_batch=[15,16,20,21,21,
21,21,21,21,21,
21,21,21,21,21,
21,21,21,22,22,
22,22,22,22,22,
23,23,23,23,23,
24,24,24,26,26,
27,27,28,35,56]

import pandas as pd
data= pd.DataFrame(age_batch)

q1=data.quantile(0.25)
q2=data.quantile(0.5)
q3=data.quantile(0.75)
IQR=(q3-q1)/2
print("first quartile is",q1.to_string())
print("second quartile is ", q2.to_string())
print("third quartile is ", q3.to_string())
print("IQR Age is ", IQR.to_string())

I am getting output as:

first quartile is 0    21.0
second quartile is  0    22.0
third quartile is  0    23.25
IQR Age is  0    1.125

there are zero printing in b/w the the string and variable<br>
why these 0's are coming and how to remove this from the output.

I tried several time but this issue is not getting resolved

The issue you're facing is due to the fact that you're using a DataFrame to store your values. When you extract a single value (like q1, q2, q3, or IQR) from the DataFrame, it retains the index. The unwanted 0 that you're seeing is the index of the single value extracted.

To resolve this and remove the unwanted zeros in the output, you can convert the extracted values to scalar values using the .iloc property to access the first (and only) element. Here's how you can modify your code to achieve this:

import pandas as pd

age_batch = [15, 16, 20, 21, 21,
             21, 21, 21, 21, 21,
             21, 21, 21, 21, 21,
             21, 21, 21, 22, 22,
             22, 22, 22, 22, 22,
             23, 23, 23, 23, 23,
             24, 24, 24, 26, 26,
             27, 27, 28, 35, 56]

data = pd.DataFrame(age_batch)

q1 = data.quantile(0.25).iloc[0]
q2 = data.quantile(0.5).iloc[0]
q3 = data.quantile(0.75).iloc[0]
IQR = (q3 - q1) / 2

print("first quartile is", q1)
print("second quartile is", q2)
print("third quartile is", q3)
print("IQR Age is", IQR)

output

first quartile is 21.0
second quartile is 22.0
third quartile is 23.25
IQR Age is 1.125

You are getting zero in starting as the quartile result for the index column from your data frame.
A quick fix will be to take out only desired column from the data frame by using indexing like -- q1[0].

import pandas as pd
data= pd.DataFrame(age_batch)

q1=data.quantile(0.25)
q2=data.quantile(0.5)
q3=data.quantile(0.75)
IQR=(q3-q1)/2
print("first quartile is", q1[0])
print("second quartile is ", q2[0])
print("third quartile is ", q3[0])
print("IQR Age is ", IQR[0])

Output

first quartile is 21.0
second quartile is  22.0
third quartile is  23.25
IQR Age is  1.125