Visualizing 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.

Tâche

Swipe to start coding

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.

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.

Assign list ['Group', 'Month', 'Temp'] as column names for transformed data within monthly_data variable.
Build the line plot 'Month' vs 'Temp' for each Group using monthly_data DataFrame.

Solution

Passez à un bureau pour une pratique réelleContinuez d'où vous êtes en utilisant l'une des options ci-dessous

Tout était clair ?

Merci pour vos commentaires !

Section 1. Chapitre 8

Visualizing the Dynamics Across Clusters

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.

Tâche

Swipe to start coding

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.

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.

Assign list ['Group', 'Month', 'Temp'] as column names for transformed data within monthly_data variable.
Build the line plot 'Month' vs 'Temp' for each Group using monthly_data DataFrame.

Solution

Passez à un bureau pour une pratique réelleContinuez d'où vous êtes en utilisant l'une des options ci-dessous

Tout était clair ?

Merci pour vos commentaires !

Section 1. Chapitre 8

Passez à un bureau pour une pratique réelleContinuez d'où vous êtes en utilisant l'une des options ci-dessous