Embedded Files
Activity 2.1.2 & 2.2:
Identify the following from your dataset and also give the reason behind it:
categorical and numerical variables
Scales of measurement of the variables
Discrete and continuous variables
2. Visualize the dataset using suitable plots. Also, provide the reasons behind choosing the respective plots and interpret the obtained trends.
Analysis of Dataset:
The data set was analysed in terms of variable type, scales of measurements, whether they are discrete or continuous, and what types of suitable plots can be made for the variable data.
The dataset has been linked in the spreadsheet.
Furthermore, plots based on the data variables has also been made in separate sheets in the same spreadsheet.
The plots analyse and present inferred trends and observations from the data.
In the section below, the graphs have been shown representing all the analysis conducted on the data.
Graphs
No. of missions per companies
To analyze the number of missions conducted by each space organization, a bar plot as is ideal for comparing categorical data like company names.
A bar plot allows for a straightforward visual comparison of mission counts across different companies, clearly highlighting which organizations have the highest or lowest number of launches.
Unlike pie charts, which can become cluttered with many categories (as shown in the sheet), the bar plot maintains clarity even with a large number of companies. The consistent axis and aligned bars make it easy to interpret differences in mission frequency, making the bar plot both efficient and informative for this type of categorical summary.
The graph plots the no. of missions per year.
For this particular analysis a line chart is best as it visually connects the number of missions year by year, making it easy to see how the number increases or decreases over time.
There are many years (1972–2020 = 40 years), line charts avoid clutter compared to bar charts/pie charts and give a cleaner visual progression.
No. of missions per year
No. of missions by launch locations
Effectively comparing the number of launches per country, a combination of a pie chart, bar chart, and map plot was used to provide different perspectives on the data.
The pie chart offers a quick, intuitive view of how each country contributes to the total number of space missions, highlighting relative proportions at a glance.
The bar chart presents a clearer, more precise comparison of launch counts across countries, making it easier to compare exact values and identify countries with significantly more or fewer launches.
Map plot adds valuable geographical context by showing launch distribution on a world map, helping to connect spatial patterns with the data.
The graph plot analyses mission status by countries.
Each segment within the bar shows how many missions were Success, Failure, Partial Failure — so you get both quantity and quality in one view.
It is also pie chart / scatter plot to classify mission status, but for this particular trend analysis, pie chart wouldn't be possible to show 3 separate values for each country, & scatter plot would be too cluttered. Hence stacked bar chart is the best option
Mission status per country
Launches during time of the day
To visualize the number of launches across different time windows (e.g., morning, afternoon, evening, night), a pie chart is an effective choice because it clearly shows the proportional distribution of launches throughout the day.
Each slice of the pie represents a specific time range, making it easy to see which part of the day had the highest or lowest launch activity.
The pie chart is especially useful here because the total (all launches) is divided into a small number of distinct categories, making it both simple and visually intuitive.
To highlight the longest and most significant missions, I used a horizontal bar chart of the top durations.
This plot effectively emphasizes the missions that lasted the longest, which may indicate deep-space missions, long-term satellite deployments, or sustained operations.
The horizontal format ensures mission names remain readable, especially if they are lengthy.
(There are missing datas for this variable in the dataset.)
Missions with longest durations
Missions from 2015 - 2020 from distinct countries
Using a line chart to visualize missions from 2015 to 2020 across distinct countries is effective because:
It shows the missions of distinct countries by increasing no. of years.
A bar chart is ideal for displaying the top 5 most-used rockets because it clearly compares the usage frequency of each rocket using easily distinguishable bars.
The horizontal or vertical bars make it simple to visually rank the rockets based on how often they were used, allowing viewers to immediately identify the most frequently launched ones.
Since bar charts are excellent for showing categorical data with count values, pie chart works too but bar charts show approx. no. while pie chart shows percentage which is not desirable for this.
Top 5 Most Used Rockets
Page updated
Google Sites
Report abuse