Lab 3.1 Making a Plot

Jose Almanza

Step 1: Examination of the Data

   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
  1.000   2.000   3.000   2.543   3.000   3.000 

  1   2   3 
 77  47 316 
   Detergents_Paper Grocery Region
1              2674    7561      3
2              3293    9568      3
3              3516    7684      3
4               507    4221      3
5              1777    7198      3
6              1795    5126      3
7              3140    6975      3
8              3321    9426      3
9              1716    6192      3
10             7425   18881      3
    Detergents_Paper Grocery Region
431              241   16483      3
432             1377    5160      3
433             1328    4754      3
434              356    1493      3
435             2371    7994      3
436              182   16027      3
437               93     764      3
438            14841   30243      3
439              168    2232      3
440              477    2510      3
 Detergents_Paper     Grocery     
 Min.   :    3.0   Min.   :    3  
 1st Qu.:  256.8   1st Qu.: 2153  
 Median :  816.5   Median : 4756  
 Mean   : 2881.5   Mean   : 7951  
 3rd Qu.: 3922.0   3rd Qu.:10656  
 Max.   :40827.0   Max.   :92780  

Data Visualization 1

Data Visualization 2

Data Visualization 3

Data Interpretation

This is a scatter plot that compares the annual spending on grocery shopping and detergents paper in three different regions, represented by different colors. The data shows a positive correlation between the money spent on grocery shopping and detergents paper across all regions. We see how people that tend to spend more money on Detergents paper also spends more money spent on Grocery shopping. Most of the data points are clustered towards the lower end of spending in both categories, with a few outliers showing higher spending. This outliers represents households in all regions apend less on both grocery shopping and detergents paper.They could families, or perhaps small business that spend a lot on these categories.

Improvements

After working with the team, I made some substantial improvements to my scatter plot. By editing the title and subtitle, I increased the graph’s readability and clarity. In addition, as instructed by the dataset, I tagged each color with the name of the associated location to improve comprehension. Additionally, I used custom CSS to improve the presenting aesthetics and visual appeal, giving our viewers a more engaging experience while adding dollar signs to guarantee that the monetary values are understood. Our audience will find the graph to be more interesting and understandable as a result.