17. Initial analyses pt 2

May 23, 2025, 3:39 PM

chapter_study_emotion.xlsx

Missing file

Load this dataset and make sure the stood_out_emotion_matches and stood_out_emotion_categories columns are readable as lists.

The columns stood_out_emotion_matches and stood_out_emotion_categories have been successfully converted to lists. Here is a preview of these columns:
  • stood_out_emotion_matches: This column contains lists of emotions that matched the user's response.
  • stood_out_emotion_categories: This column contains lists of categories for the emotions that stood out.
If you have any more questions or need further analysis, feel free to ask!

Set blank lists in stood_out_emotion_matches and stood_out_emotion_categories to missing.

The empty lists in the columns stood_out_emotion_matches and stood_out_emotion_categories have been successfully replaced with missing values (None). This ensures that any analysis or operations on these columns will treat these entries as missing data.
If you have any further questions or need additional analysis, feel free to ask!

Create a bar chart that shows the top 6 emotion categories by character identification quartile. Exclude missing responses as well as the categories observant and beautystruck.

Group the quartile bars together on the x-axis and remove the emotion labels from the axis. Put the emotion labels in the legend.

Recreate this chart to show the 6 most frequently occurring emotion categories by quartile.

Create a bar chart that shows the most frequently-occurring emotion categories for each character identification quartile.

Create a bar chart that shows the six most frequently-occurring emotion categories for each character identification quartile.

Remove gaps in that chart. Make sure the bars for a given quartile are contiguous.

Do not stack the bars.

Label the bars with the names of the emotions from the legend

keep the bars stacked

put the raw counts in the stacked bar labels and remove the labels from the y-axis

remove the tick marks from the y axis and put the legend labels in next to the raw counts in the bars

arrange the bar stacks from largest count at the bottom to lowest count at the top

order the different emotion categories in the bars so that they stack in ascending order

order the different emotion categories in the bars so that they stack in descending order based on raw counts

relabel the x-axis ticks so that they read Lowest, Second, Third, and Highest

Add a label to the y axis that says "frequency of mention"

show me the distribution of character identification quartiles by chapter

Run a chi-square test to determine if the actual count of people from a given character identification quartile assigned to a given chapter is significantly different from the expected number.

The chi-square test results are as follows:
  • Chi-square statistic: 24.96
  • p-value: 0.249
  • Degrees of freedom: 21
The p-value of 0.249 suggests that there is no statistically significant difference between the observed and expected counts of people from different character identification quartiles assigned to each chapter. This means that the distribution of character identification quartiles across chapters is not significantly different from what would be expected by chance.
If you have any more questions or need further analysis, feel free to ask!

Within each chapter, what are the top 3 most frequently occurring emotions (excluding beautystruck and observant)?

Within each chapter, the top 3 most frequently occurring emotions (excluding 'beautystruck' and 'observant') are as follows:
  • Atacama: Interested (17), Inspired (12), Happy (11)
  • Greenland: Interested (13), Calm (9), Bored (8)
  • Maine: Calm (14), Interested (14), Happy (6)
  • Minnesota: Calm (17), Interested (14), Respectful (11)
  • Pantalica: Interested (23), Calm (10), Happy (9)
  • Senegal: Happy (10), Calm (9), Touched (9)
  • Seoul: Interested (17), Inspired (13), Captivated (9)
  • Southwest: Interested (30), Surprised (7), Approving (6)
If you have any more questions or need further analysis, feel free to ask!

Can you express the counts in that table as percentages, where the percentage is calculated as (count)/(total responses within that chapter where emotional categories were not blank)?

The top 3 most frequently occurring emotions within each chapter, expressed as percentages of the total responses where emotional categories were not blank, are as follows:
  • Atacama:
    • Interested: 22.08%
    • Inspired: 15.58%
    • Happy: 14.29%
  • Greenland:
    • Interested: 14.77%
    • Calm: 10.23%
    • Bored: 9.09%
  • Maine:
    • Calm: 20.59%
    • Interested: 20.59%
    • Happy: 8.82%
  • Minnesota:
    • Calm: 21.25%
    • Interested: 17.50%
    • Respectful: 13.75%
  • Pantalica:
    • Interested: 28.75%
    • Calm: 12.50%
    • Happy: 11.25%
  • Senegal:
    • Happy: 16.39%
    • Calm: 14.75%
    • Touched: 14.75%
  • Seoul:
    • Interested: 18.48%
    • Inspired: 14.13%
    • Captivated: 9.78%
  • Southwest:
    • Interested: 36.59%
    • Surprised: 8.54%
    • Approving: 7.32%
If you have any more questions or need further analysis, feel free to ask!

Round those percentages to whole numbers

The top 3 most frequently occurring emotions within each chapter, expressed as percentages of the total responses where emotional categories were not blank and rounded to whole numbers, are as follows:
  • Atacama:
    • Interested: 22%
    • Inspired: 16%
    • Happy: 14%
  • Greenland:
    • Interested: 15%
    • Calm: 10%
    • Bored: 9%
  • Maine:
    • Calm: 21%
    • Interested: 21%
    • Happy: 9%
  • Minnesota:
    • Calm: 21%
    • Interested: 18%
    • Respectful: 14%
  • Pantalica:
    • Interested: 29%
    • Calm: 12%
    • Happy: 11%
  • Senegal:
    • Happy: 16%
    • Calm: 15%
    • Touched: 15%
  • Seoul:
    • Interested: 18%
    • Inspired: 14%
    • Captivated: 10%
  • Southwest:
    • Interested: 37%
    • Surprised: 9%
    • Approving: 7%
If you have any more questions or need further analysis, feel free to ask!
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