Perform T-Test in Pandas

Perform T-Test in Pandas

This tutorial will discuss how we can find T-test values in Pandas.

Steps to Perform T-Test in Pandas

The following are the steps to perform a T-test in Pandas.

Import Pertinent Libraries

We must import the Pandas library and ttest_ind from scipy.stats to get started.

import pandas as pd
from scipy.stats import ttest_ind

Create a Pandas DataFrame

Let us create a sample dataframe to perform the T-test operation on the same dataframe.

data = {'Category': ['type2','type1','type2','type1','type2','type1','type2','type1','type1','type1','type2'], 'values': [1,2,3,1,2,3,1,2,3,5,1]}
df = pd.DataFrame(data)

We created a dataframe with a category column with two types of categories and assigned a value to each category instance.

Let us view our dataframe below.



   Category  values
0     type2       1
1     type1       2
2     type2       3
3     type1       1
4     type2       2
5     type1       3
6     type2       1
7     type1       2
8     type1       3
9     type1       5
10    type2       1

We will now create a separate data frame for both category types using the below code. This step facilitates the T-test finding procedure.

type1 = my_data[my_data['Category']=='type1']
type2 = my_data[my_data['Category']=='type2']

Obtain T-Test Values in Pandas

We will now find the T-test results and store them in a variable using the ttest_ind() function. We use this function in the following way.

res = ttest_ind(type1['values'], type2['values'])

In the above code, we passed our data frames to the function as a parameter, and we got the T-test results, including a tuple with the t-statistic & the p-value.

Let us now print the res variable to see the results.



Ttest_indResult(statistic=1.4927289925706944, pvalue=0.16970867501294376)

In the above output, we have found the T-test values with the t-statistic and the p-value. Thus, we can successfully find the T-test values in Pandas with the above method.

Preet Sanghavi avatar Preet Sanghavi avatar

Preet writes his thoughts about programming in a simplified manner to help others learn better. With thorough research, his articles offer descriptive and easy to understand solutions.

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