fresh shadow Oct 21, 2024, 1:52 AM

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My professor basically told me to go F myself when I asked him for help with this assignment. I have to use screen shots. The output is not what is expected.

steady lagoonBOT Oct 21, 2024, 1:52 AM

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fresh shadow My professor basically told me to go F myself when I asked him for help with thi...

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@fresh shadow

Python help channel opened

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Ask your Python question, not if you can ask or if there's an expert who can help.
Show a code sample as text (rather than a screenshot) and the error message, if you've got one.
Explain what you expect to happen and what actually happens.

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fresh shadow Oct 21, 2024, 1:53 AM

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here's the instructions

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here's the code I have

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and here's what the expected outcome is.

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Simple Linear Regression Model.

thin crown Oct 21, 2024, 1:57 AM

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What's your question tho?

fresh shadow Oct 21, 2024, 1:57 AM

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I keep getting a different outcome then what is expected. Look at the screen shots.

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My question is what and where exactly am I doing wrong?

thin crown Oct 21, 2024, 1:58 AM

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Paste text plz, too hard to review code from ss

fresh shadow Oct 21, 2024, 1:58 AM

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okay .

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import pandas as pd
import numpy as np
from sklearn.linear_model import LinearRegression

# Read in nbaallelo_slr.csv
nba =  pd.read_csv('nbaallelo_slr.csv')

# Create a new column in the data frame that is the difference between pts and opp_pts
nba['y'] = nba['pts'] - nba ['opp_pts']


# Store relevant columns as variables
X = nba[['pts']].values.reshape(-1,1)
y = nba[['opp_pts']].values.reshape(-1,1)

# Initialize the linear regression model
SLRModel = LinearRegression()
# Fit the model on X and y
SLRModel.fit(X, y)

# Print the intercept
intercept = SLRModel.intercept_
print('The intercept of the linear regression line is ', end="")
print('%.3f' % intercept[0] + ". ")

# Print the slope
slope = SLRModel.coef_
print('The slope of the linear regression line is ', end="")
print('%.3f' % slope[0][0] + ". ")

# Compute the proportion of variation explained by the linear regression using the LinearRegression object's score method
score = SLRModel.score(X, y)
print('The proportion of variation explained by the linear regression model is ', end="")
print('%.3f' % score + ". ")

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there.

thin crown Oct 21, 2024, 1:59 AM

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But glancing, you're not following instructions.

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What is your X and y supposed to be, given first instructions

fresh shadow Oct 21, 2024, 2:00 AM

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okay exactly where and how?

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Load the dataset into a data frame.
Create a new column y in the data frame that is the difference between the points made by the two teams.
Use sklearn's LinearRegression() function to perform a simple linear regression on the y and elo_i columns.
Compute the proportion of variation explained by the linear regression using the LinearRegression object's score method.

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these are the instructions. Their also in the screen shot.

thin crown Oct 21, 2024, 2:01 AM

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What is 'y' supposed to be?

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Use your words.

fresh shadow Oct 21, 2024, 2:02 AM

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you mean this?

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Create a new column in the data frame that is the difference between pts and opp_pts

nba['y'] = nba['pts'] - nba ['opp_pts']

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-_-

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'''py # Create a new column in the data frame that is the difference between pts and opp_pts
nba['y'] = nba['pts'] - nba ['opp_pts']
'''

thin crown Oct 21, 2024, 2:04 AM

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What is 'y' supposed to represent?

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I'm giving you the hint/answer that there's a mistake related to how you use y.

fresh shadow Oct 21, 2024, 2:06 AM

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I dont know what you mean?

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I'm lost.

thin crown Oct 21, 2024, 2:06 AM

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fresh shadow I dont know what you mean?

In your words, what is y supposed to be?

fresh shadow Oct 21, 2024, 2:06 AM

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I don't know to tell you the truth.

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there's no csv file to download if there was this would be easier.

thin crown Oct 21, 2024, 2:07 AM

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Y is the difference between pts and opposing pts. That's what the instructions say.

fresh shadow Oct 21, 2024, 2:07 AM

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yes and I did that.

thin crown Oct 21, 2024, 2:07 AM

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Now, what 'y' are you passing to fit?

fresh shadow Oct 21, 2024, 2:07 AM

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hold on.

thin crown Oct 21, 2024, 2:08 AM

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fresh shadow yes and I did that.

But... you never use the new y column you created.

fresh shadow Oct 21, 2024, 2:08 AM

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how?

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wait hold on.

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alright I'm on to something.

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Now I just have to get X to fit.

thin crown Oct 21, 2024, 2:09 AM

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Good, because your X is also wrong

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Again, read instructions and then look at what X you're passing to fit

fresh shadow Oct 21, 2024, 2:10 AM

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wow. I'm dumber than I thought. XD

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okay so X can't be 'pts'.

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so X must be either elo_i or elo_n

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try them both i guess.

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alright I got it finally.

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thank you.

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nothing is ever simple in python. XD

thin crown Oct 21, 2024, 2:12 AM

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Just remember, pebkac

fresh shadow Oct 21, 2024, 2:13 AM

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that's how you know you work with computers. the constant tic tak of the keyboard, and the frustration to pull out your hair. Which sucks for me since I have short hair.

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PEBKAC is an acronym for "Problem Exists Between Keyboard and Chair"

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story of my god d*mn life.

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always the simple mistakes.

steady lagoonBOT Oct 21, 2024, 3:14 AM

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Python help channel closed

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#🔒 Simple Regression Model.

Create a new column in the data frame that is the difference between pts and opp_pts