From 3d161b77b76d3106a4e80f3fa51696e51509f9ce Mon Sep 17 00:00:00 2001 From: Savi Dahegaonkar Date: Wed, 7 Aug 2024 01:19:37 +0530 Subject: [PATCH 1/7] New file has been added. --- .../dart/concepts/user-input/user-input.md | 56 +++++++++++++++++++ 1 file changed, 56 insertions(+) create mode 100644 content/dart/concepts/user-input/user-input.md diff --git a/content/dart/concepts/user-input/user-input.md b/content/dart/concepts/user-input/user-input.md new file mode 100644 index 00000000000..10c685392cd --- /dev/null +++ b/content/dart/concepts/user-input/user-input.md @@ -0,0 +1,56 @@ +--- +Title: 'user-input' +Description: 'User input in Dart is used to read the data from console and interact with the web applications.' +Subjects: + - 'Code Foundations' + - 'Computer Science' + - 'Mobilr Development' +Tags: + - 'Dart' + - 'Input' + - 'Flutter' + - 'Console' + - 'Forms' +CatalogContent: + - 'learn-dart' + - 'paths/computer-science' +--- + +**User input** is the most basic aspect of intearction between the user and the software. In Dart it varied depending on the type of application being used. It can be a web application, a Flutter or a console application. Dart provides varitey of tools and libraried to manage the user input effectively. + +## Syntax + +```pseudo +import 'dart:io'; + +void main(){ + String? input = stdin.readLineSync(); +} +``` + + +## Example + +The below code shows the implementation of user input in dart. It inputs a value as an age from the user and generates it as output: + +```dart +import 'dart:io'; +void main(){ + stdout.write('Enter your age: '); + String? input=stdin.readLineSync(); + + if(input !=null){ + int age=int.parse(input); + print('Dear Friend, You are $age years old.'); + }else{ + print('Invalid input.'); + } +} +``` + +The above code produces the following output: + +```shell +Enter your age: 21 +Dear Friend, You are 21 years old. +``` \ No newline at end of file From 5a211ba5d71aa65c6e98a37185912f4dc02f63a7 Mon Sep 17 00:00:00 2001 From: shantanu <56212958+cigar-galaxy82@users.noreply.github.com> Date: Sun, 8 Sep 2024 06:40:43 +0530 Subject: [PATCH 2/7] Update user-input.md --- .../dart/concepts/user-input/user-input.md | 31 +++++++++---------- 1 file changed, 14 insertions(+), 17 deletions(-) diff --git a/content/dart/concepts/user-input/user-input.md b/content/dart/concepts/user-input/user-input.md index 10c685392cd..7c460739ab7 100644 --- a/content/dart/concepts/user-input/user-input.md +++ b/content/dart/concepts/user-input/user-input.md @@ -1,23 +1,22 @@ --- -Title: 'user-input' -Description: 'User input in Dart is used to read the data from console and interact with the web applications.' +Title: 'User Input' +Description: 'User input in Dart is used to read the data from the console and interact with the web applications.' Subjects: - 'Code Foundations' - 'Computer Science' - - 'Mobilr Development' + - 'Mobile Development' Tags: - 'Dart' - 'Input' - 'Flutter' - 'Console' - - 'Forms' + - 'Form' CatalogContent: - 'learn-dart' - 'paths/computer-science' --- -**User input** is the most basic aspect of intearction between the user and the software. In Dart it varied depending on the type of application being used. It can be a web application, a Flutter or a console application. Dart provides varitey of tools and libraried to manage the user input effectively. - +**User input** is a fundamental aspect of interaction between users and software. In Dart, it varies depending on the type of application being used. It can be a web application, a Flutter application, or a console application. Dart provides a variety of tools and libraries to manage user input effectively. ## Syntax ```pseudo @@ -28,22 +27,20 @@ void main(){ } ``` - ## Example -The below code shows the implementation of user input in dart. It inputs a value as an age from the user and generates it as output: +The below code shows the implementation of user input in Dart. It inputs a value as an age from the user and generates an output: ```dart import 'dart:io'; -void main(){ +void main() { stdout.write('Enter your age: '); - String? input=stdin.readLineSync(); - - if(input !=null){ - int age=int.parse(input); - print('Dear Friend, You are $age years old.'); - }else{ - print('Invalid input.'); + String? input = stdin.readLineSync(); + if (input != null) { + int age = int.parse(input); + print('Dear Friend, You are $age years old.'); + } else { + print('Invalid input.'); } } ``` @@ -53,4 +50,4 @@ The above code produces the following output: ```shell Enter your age: 21 Dear Friend, You are 21 years old. -``` \ No newline at end of file +``` From 5923e4e82717287d92c33239edac66e03d84edb4 Mon Sep 17 00:00:00 2001 From: shantanu <56212958+cigar-galaxy82@users.noreply.github.com> Date: Sun, 8 Sep 2024 06:42:57 +0530 Subject: [PATCH 3/7] Update user-input.md --- content/dart/concepts/user-input/user-input.md | 1 + 1 file changed, 1 insertion(+) diff --git a/content/dart/concepts/user-input/user-input.md b/content/dart/concepts/user-input/user-input.md index 7c460739ab7..fbaf8a79327 100644 --- a/content/dart/concepts/user-input/user-input.md +++ b/content/dart/concepts/user-input/user-input.md @@ -17,6 +17,7 @@ CatalogContent: --- **User input** is a fundamental aspect of interaction between users and software. In Dart, it varies depending on the type of application being used. It can be a web application, a Flutter application, or a console application. Dart provides a variety of tools and libraries to manage user input effectively. + ## Syntax ```pseudo From 37bc4f957f17f34e5163af9de8e9e8a1601fb369 Mon Sep 17 00:00:00 2001 From: Savi Dahegaonkar Date: Tue, 3 Dec 2024 01:24:11 +0530 Subject: [PATCH 4/7] File has been modified. --- .../concepts/statsmodels/terms/ols/ols.md | 79 +++++++++++++++++++ 1 file changed, 79 insertions(+) create mode 100644 content/python/concepts/statsmodels/terms/ols/ols.md diff --git a/content/python/concepts/statsmodels/terms/ols/ols.md b/content/python/concepts/statsmodels/terms/ols/ols.md new file mode 100644 index 00000000000..ab926cd043a --- /dev/null +++ b/content/python/concepts/statsmodels/terms/ols/ols.md @@ -0,0 +1,79 @@ +--- +Title: 'Ordinary Least Squares' +Description: 'Uses Ordinary Least Squares (OLS) to perform linear regression in order to reduce prediction errors and evaluate associations between variables.' +Subjects: + - 'Computer Science' + - 'Data Science' + - 'Data Visualization' + - 'Machine Learning' +Tags: + - 'Data' + - 'Linear Regression' + - 'Machine Learning' +CatalogContent: + - 'learn-python-3' + - 'paths/data-science-foundations' +--- + +**Ordinary least squares** (OLS) is a statistical method that reduces the sum of squared residuals to assess the correlation between independent and dependent variables. In linear regression, it is widely used to predict values and analyze correlations between variables. + +## Syntax + +Here's syntax to implement Ordinary Least Squares in Python: + +```pseudo + +import statsmodels.api as sm # Import the statsmodels library + +# Add a constant to the independent variable(s) for the intercept +X = sm.add_constant(X) # Method to add a constant to X + +# Fit the OLS model +model = sm.OLS(y, X).fit() # `OLS` function applied to y (dependent variable) and X (independent variables) + +# Access the model summary +model.summary() # Method to get summary statistics +``` +- `sm.add_constant(x)`: Adds an intercept (constant term) to the independent variables X. +- `sm.OLS(y, X)`: Creates the OLS model with y as the dependent variable and X as the independent variables. +- `model.summary()`: Displays the model's results, including coefficients and `R-squared`values. + +## Example + +Here's an example predicting `test_scores` based on `hours_studied`: + +```py +import statsmodels.api as sm +import matplotlib.pyplot as plt +import numpy as np + +# Hours studied and corresponding test scores +hours_studied = [1, 2, 3, 4, 5] +test_scores = [50, 55, 60, 65, 70] + +# Add a constant to the independent variable +hours_with_constant = sm.add_constant(hours_studied) + +# Fit the OLS model +model = sm.OLS(test_scores, hours_with_constant).fit() + +# Display the summary of the model +print(model.summary()) + +# Predict the test scores using OLS model +predicted_scores = model.predict(hours_with_constant) + +# Plot the data and line +plt.scatter(hours_studied, test_scores, color='blue', label='Observed data') +plt.plot(hours_studied, predicted_scores, color='red', label='Fitted line') + +# Displaying the plot +plt.xlabel('Hours Studied') +plt.ylabel('Test Scores') +plt.title('OLS Regression: Test Scores vs Hours Studied') +plt.legend() + +# Show the plot +plt.show() +``` +[Regression plot](https://raw.githubusercontent.com/Codecademy/docs/main/media/ols-model-example.png) \ No newline at end of file From 7e6d146e9331addaeb359653f97a00fee007c4d2 Mon Sep 17 00:00:00 2001 From: Savi Dahegaonkar <124272050+SaviDahegaonkar@users.noreply.github.com> Date: Wed, 4 Dec 2024 17:22:39 +0530 Subject: [PATCH 5/7] Update content/python/concepts/statsmodels/terms/ols/ols.md Co-authored-by: Daksha Deep --- content/python/concepts/statsmodels/terms/ols/ols.md | 1 - 1 file changed, 1 deletion(-) diff --git a/content/python/concepts/statsmodels/terms/ols/ols.md b/content/python/concepts/statsmodels/terms/ols/ols.md index ab926cd043a..9c3a2527078 100644 --- a/content/python/concepts/statsmodels/terms/ols/ols.md +++ b/content/python/concepts/statsmodels/terms/ols/ols.md @@ -22,7 +22,6 @@ CatalogContent: Here's syntax to implement Ordinary Least Squares in Python: ```pseudo - import statsmodels.api as sm # Import the statsmodels library # Add a constant to the independent variable(s) for the intercept From 09b6d786031cbf1989fc7ee9485f360817efe7fc Mon Sep 17 00:00:00 2001 From: Savi Dahegaonkar <124272050+SaviDahegaonkar@users.noreply.github.com> Date: Wed, 4 Dec 2024 17:24:49 +0530 Subject: [PATCH 6/7] Update content/python/concepts/statsmodels/terms/ols/ols.md Co-authored-by: Daksha Deep --- content/python/concepts/statsmodels/terms/ols/ols.md | 1 + 1 file changed, 1 insertion(+) diff --git a/content/python/concepts/statsmodels/terms/ols/ols.md b/content/python/concepts/statsmodels/terms/ols/ols.md index 9c3a2527078..dc8e3c9bd99 100644 --- a/content/python/concepts/statsmodels/terms/ols/ols.md +++ b/content/python/concepts/statsmodels/terms/ols/ols.md @@ -33,6 +33,7 @@ model = sm.OLS(y, X).fit() # `OLS` function applied to y (dependent variable) a # Access the model summary model.summary() # Method to get summary statistics ``` + - `sm.add_constant(x)`: Adds an intercept (constant term) to the independent variables X. - `sm.OLS(y, X)`: Creates the OLS model with y as the dependent variable and X as the independent variables. - `model.summary()`: Displays the model's results, including coefficients and `R-squared`values. From c88b733c28b88f0ce7060f5348f97909c013f63b Mon Sep 17 00:00:00 2001 From: Savi Dahegaonkar Date: Wed, 4 Dec 2024 18:26:43 +0530 Subject: [PATCH 7/7] Added the changes. --- .../concepts/statsmodels/terms/ols/ols.md | 13 +++++++------ media/ols-model-example.png | Bin 0 -> 32189 bytes 2 files changed, 7 insertions(+), 6 deletions(-) create mode 100644 media/ols-model-example.png diff --git a/content/python/concepts/statsmodels/terms/ols/ols.md b/content/python/concepts/statsmodels/terms/ols/ols.md index dc8e3c9bd99..6dcb36866cd 100644 --- a/content/python/concepts/statsmodels/terms/ols/ols.md +++ b/content/python/concepts/statsmodels/terms/ols/ols.md @@ -1,6 +1,6 @@ --- -Title: 'Ordinary Least Squares' -Description: 'Uses Ordinary Least Squares (OLS) to perform linear regression in order to reduce prediction errors and evaluate associations between variables.' +Title: 'Ordinary Least Squares' +Description: 'Uses Ordinary Least Squares (OLS) to perform linear regression in order to reduce prediction errors and evaluate associations between variables.' Subjects: - 'Computer Science' - 'Data Science' @@ -10,12 +10,12 @@ Tags: - 'Data' - 'Linear Regression' - 'Machine Learning' -CatalogContent: +CatalogContent: - 'learn-python-3' - 'paths/data-science-foundations' --- -**Ordinary least squares** (OLS) is a statistical method that reduces the sum of squared residuals to assess the correlation between independent and dependent variables. In linear regression, it is widely used to predict values and analyze correlations between variables. +**Ordinary least squares** (OLS) is a statistical method that reduces the sum of squared residuals to assess the correlation between independent and dependent variables. In linear regression, it is widely used to predict values and analyze correlations between variables. ## Syntax @@ -48,7 +48,7 @@ import matplotlib.pyplot as plt import numpy as np # Hours studied and corresponding test scores -hours_studied = [1, 2, 3, 4, 5] +hours_studied = [1, 2, 3, 4, 5] test_scores = [50, 55, 60, 65, 70] # Add a constant to the independent variable @@ -76,4 +76,5 @@ plt.legend() # Show the plot plt.show() ``` -[Regression plot](https://raw.githubusercontent.com/Codecademy/docs/main/media/ols-model-example.png) \ No newline at end of file + +! 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