1) Sales and Revenue Analysis
Scenario: A business analyzes monthly sales, revenue, and marketing expenses for a product over six months.
Data Example:
Month |
January |
February |
March |
April |
May |
June |
Sales (Units) |
100 |
120 |
140 |
160 |
180 |
200 |
Revenue (USD) |
500 |
600 |
700 |
800 |
900 |
920 |
Marketing Expenses (USD) |
100 |
120 |
150 |
180 |
200 |
250 |
Operational Expenses (USD) |
200 |
300 |
400 |
500 |
600 |
700 |
R&D Expenses (USD) |
500 |
700 |
900 |
930 |
950 |
980 |
Purpose: The multi axes line graph compares the sales, revenue, and marketing expenses over six months, helping the company identify trends and fluctuations in these key business metrics.
Download the
file and upload it through the CSV tool to create a multi-axes line graph displaying the complete financial analysis of the business performance.
2) Hospital Patient Trends
Scenario: A hospital monitors patient admissions, average length of stay, and resource usage (e.g., beds) over six months to optimize operations.
Data Example:
Month |
January |
February |
March |
April |
May |
June |
Patient Admissions (No of Patients) |
120 |
110 |
130 |
140 |
135 |
125 |
Physician Response Time (Minutes) |
15 |
16 |
17 |
18 |
19 |
Bed Usage (%) |
85 |
80 |
90 |
95 |
88 |
82 |
Discharge Rate (%) |
75 |
80 |
78 |
85 |
82 |
79 |
Resource Utilization(%) |
88 |
85 |
90 |
92 |
89 |
87 |
Purpose: To understand how patient flow and average length of stay impact bed availability and hospital resources, supporting improved patient care and operational efficiency.
Click here to download the
file and use the CSV tool to generate a line graph visualizing the hospital's performance across the months.
3) Airline Performance Analysis
Scenario: An airline wants to visualize the impact of flight delays on passenger satisfaction and operational performance over six months. By analyzing this data, they can identify trends, address service issues, and improve overall efficiency.
Data Example:
Month |
January |
February |
March |
April |
May |
June |
Avg. Flight Delay (min) |
15 |
20 |
25 |
30 |
35 |
40 |
Passenger Satisfaction (%) |
85 |
80 |
75 |
72 |
68 |
65 |
Total Flights |
1200 |
1250 |
1300 |
1350 |
1400 |
1450 |
Complaints |
50 |
75 |
100 |
130 |
160 |
200 |
On-Time Performance (%) |
90 |
87 |
85 |
82 |
78 |
75 |
Purpose: A multi axes line graph helps visualize how increasing flight delays negatively impact passenger satisfaction while also affecting on-time performance and customer complaints. The graph allows the airline to monitor trends, optimize schedules, and improve operational efficiency.
To gain deeper insights, download the
file and upload it into the above CSV option to generate a detailed multi axes line graph visualization.