Hello Guys, How are you all? Hope You all Are Fine. Today We Are Going To learn about **How to extract the regression coefficient from statsmodels.api** **in Python**. So Here I am Explain to you all the possible Methods here.

Without wasting your time, Let’s start This Article.

Table of Contents

## How to extract the regression coefficient from statsmodels.api?

**How to extract the regression coefficient from statsmodels.api?**Cribbing from this answer Converting statsmodels summary object to Pandas Dataframe, it seems that the result.summary() is a set of tables

**extract the regression coefficient from statsmodels.api**Cribbing from this answer Converting statsmodels summary object to Pandas Dataframe, it seems that the result.summary() is a set of tables

## Method 1

You can use the `params`

property of a fitted model to get the coefficients.

For example, the following code:

import statsmodels.api as sm import numpy as np np.random.seed(1) X = sm.add_constant(np.arange(100)) y = np.dot(X, [1,2]) + np.random.normal(size=100) result = sm.OLS(y, X).fit() print(result.params)

will print you a numpy array `[ 0.89516052 2.00334187]`

– estimates of intercept and slope respectively.

If you want more information, you can use the object `result.summary()`

that contains 3 detailed tables with model description.

## Method 2

Cribbing from this answer Converting statsmodels summary object to Pandas Dataframe, it seems that the result.summary() is a set of tables, which you can export as html and then use Pandas to convert to a dataframe, which will allow you to directly index the values you want.

So, for your case (putting the answer from the above link into one line):

df = pd.read_html(result.summary().tables[1].as_html(),header=0,index_col=0)[0]

And then

a=df['coef'].values[1] c=df['coef'].values[0]

**Summery**

It’s all About this issue. Hope all Methods helped you a lot. Comment below Your thoughts and your queries. Also, Comment below which Method worked for you? Thank You.

**Also, Read**