How do I change this R code to Python?

import numpy as np

import pandas as pd

import matplotlib.pyplot as plt

import seaborn as sns

from scipy import stats

from statsmodels.api import OLS

$$

# Assuming data loading and creation is done similarly

# Example: Importing data using pandas

# Replace $`"$C:$/$Users$/$slaug$/$Downloads$/$MIS$470$GDP$.$xls$"`$ with the actual path to your Excel file

MIS$470$GDP $=$ pd$.$read$\_$excel$("$C:$/$Users$/$slaug$/$Downloads$/$MIS$470$GDP$.$xls$")$

$$

# Generate random data for the example as in original R code

np$.$random.seed$(123)$

n $=100$

GDP $=$ np$.$random.uniform$(10000,100000,$ n$)$

true$\_$intercept $=5000$

true$\_$slope $=0\mathrm{.}1$

noise $=$ np$.$random.normal$(0,3000,$ n$)$

USEUR $=$ true$\_$intercept $+$ true$\_$slope $*$ GDP $+$ noise

$$

# Create a DataFrame

data $=$ pd$.$DataFrame$(\{\text{'}$GDP$\text{'}$: GDP$,$ 'USEUR': USEUR$\})$

$$

# View the first few rows of the data

print$($data$.$head$())$

$$

# Scatter plot of GDP vs$.$ USEUR

plt$.$figure$($figsize$=(10,6))$

sns$.$scatterplot$($data$=$data, x$=\text{'}$GDP$\text{'},$ y$=$'USEUR'$)$

plt$.$title$("$Scatter Plot of GDP vs$.$ USEUR"$)$

plt$.$xlabel$(\text{'}$GDP$\text{'})$

plt$.$ylabel$(\text{'}$USEUR$\text{'})$

plt$.$show$()$

$$

# Fit the linear regression model

X $=$ data$[\text{'}$GDP$\text{'}]$

y $=$ data$[\text{'}$USEUR$\text{'}]$

X $=$ np$.$add$\_$constant$($X$)$ # adding a constant for intercept

model $=$ OLS$($y$,$ X$).$fit$()$

$$

# Summary of the model

print$($model$.$summary$())$

$$

# Predict USEUR for a new GDP value

new$\_$data $=$ pd$.$DataFrame$(\{\text{'}$GDP$\text{'}$: $[22007\mathrm{.}372]\})$

new$\_$data $=$ np$.$add$\_$constant$($new$\_$data$)$ # adding a constant for intercept

predicted$\_$USEUR $=$ model.predict$($new$\_$data$)$

print$($f$\text{'}$Predicted USEUR for GDP $=22007\mathrm{.}372$ is $\{$predicted$\_$USEUR$[0]\}\text{'})$

$$

# Create the scatter plot with regression line

plt$.$figure$($figsize$=(10,6))$

sns$.$scatterplot$($data$=$data, x$=\text{'}$GDP$\text{'},$ y$=$'USEUR'$)$

sns$.$lineplot$($x$=\text{'}$GDP$\text{'},$ y$=$model.fittedvalues, data$=$data, color$=$'blue', label$=$'Fitted line'$)$

plt$.$title$("$Scatter Plot with Linear Regression Line"$)$

plt$.$xlabel$(\text{'}$GDP$\text{'})$

plt$.$ylabel$(\text{'}$USEUR$\text{'})$

plt$.$show$()$

$$

# $90\%$ Confidence Interval

confidence$\_$level $=0\mathrm{.}90$

degrees$\_$freedom $=$ len$($data$)-2$

confidence$\_$interval $=$ stats.t$.$interval$($confidence$\_$level, degrees$\_$freedom, loc$=$model.params$[1],$ scale$=$model.bse$[1])$

print$($f$"90\%$ Confidence Interval: $[\{$round$($confidence$\_$interval$[0],2)\},\{$round$($confidence$\_$interval$[1],2)\}]")$