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

Sveip for å vise menyen

book
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.

Oppgave

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.

Løsning

Switch to desktopBytt til skrivebordet for virkelighetspraksisFortsett der du er med et av alternativene nedenfor
Alt var klart?

Hvordan kan vi forbedre det?

Takk for tilbakemeldingene dine!

Seksjon 1. Kapittel 8
Vi beklager at noe gikk galt. Hva skjedde?

Spør AI

expand
ChatGPT

Spør om hva du vil, eller prøv ett av de foreslåtte spørsmålene for å starte chatten vår

book
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.

Oppgave

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.

Løsning

Switch to desktopBytt til skrivebordet for virkelighetspraksisFortsett der du er med et av alternativene nedenfor
Alt var klart?

Hvordan kan vi forbedre det?

Takk for tilbakemeldingene dine!

Seksjon 1. Kapittel 8
Switch to desktopBytt til skrivebordet for virkelighetspraksisFortsett der du er med et av alternativene nedenfor
Vi beklager at noe gikk galt. Hva skjedde?
some-alt