Notice: This page requires JavaScript to function properly.
Please enable JavaScript in your browser settings or update your browser.
Вивчайте Visualizing the Dynamics Across Clusters | K-Means Algorithm
Cluster Analysis in Python

bookVisualizing the Dynamics Across Clusters

The selective pair of months on the scatter plot looked good, didn't it? Maybe there were no key differences between 'areas' on the plot, but at least there were no outliers outside the respective groups, and in general, all groups were disjoint.

Finally, let's find out the yearly dynamics for each cluster, i.e. let's build the line plot representing the monthly averages for each group of points.

Завдання

Swipe to start coding

Table
  1. Extract the necessary columns (month's names and temperatures) within the col variable:
  • Firstly, extract the 2-13 column names as list type, and save them within the col variable.
  • Then add the 'prediction' string to the list col.
  1. Calculate the monthly average temperatures for each cluster, and save the result within monthly_data variable:
  • Firstly group the observations of col column of data by 'prediction'.
  • Then calculate .mean() of grouped table.
  • Then apply .stack() to stack the table (already done).
  • Finally reset the indices using .reset_index() method.
  1. Assign list ['Group', 'Month', 'Temp'] as column names for transformed data within monthly_data variable.

  2. Build the line plot 'Month' vs 'Temp' for each Group using monthly_data DataFrame.

Рішення

Все було зрозуміло?

Як ми можемо покращити це?

Дякуємо за ваш відгук!

Секція 1. Розділ 8
single

single

Запитати АІ

expand

Запитати АІ

ChatGPT

Запитайте про що завгодно або спробуйте одне із запропонованих запитань, щоб почати наш чат

Suggested prompts:

Сумаризуйте цей розділ

Пояснити код у file

Пояснити, чому file не вирішує завдання

close

Awesome!

Completion rate improved to 3.57

bookVisualizing the Dynamics Across Clusters

Свайпніть щоб показати меню

The selective pair of months on the scatter plot looked good, didn't it? Maybe there were no key differences between 'areas' on the plot, but at least there were no outliers outside the respective groups, and in general, all groups were disjoint.

Finally, let's find out the yearly dynamics for each cluster, i.e. let's build the line plot representing the monthly averages for each group of points.

Завдання

Swipe to start coding

Table
  1. Extract the necessary columns (month's names and temperatures) within the col variable:
  • Firstly, extract the 2-13 column names as list type, and save them within the col variable.
  • Then add the 'prediction' string to the list col.
  1. Calculate the monthly average temperatures for each cluster, and save the result within monthly_data variable:
  • Firstly group the observations of col column of data by 'prediction'.
  • Then calculate .mean() of grouped table.
  • Then apply .stack() to stack the table (already done).
  • Finally reset the indices using .reset_index() method.
  1. Assign list ['Group', 'Month', 'Temp'] as column names for transformed data within monthly_data variable.

  2. Build the line plot 'Month' vs 'Temp' for each Group using monthly_data DataFrame.

Рішення

Switch to desktopПерейдіть на комп'ютер для реальної практикиПродовжуйте з того місця, де ви зупинились, використовуючи один з наведених нижче варіантів
Все було зрозуміло?

Як ми можемо покращити це?

Дякуємо за ваш відгук!

close

Awesome!

Completion rate improved to 3.57
Секція 1. Розділ 8
single

single

some-alt