Creating Multi-Line Time Series Charts in Apache Superset

  

In many real-world scenarios, data doesn’t come from a single source, it’s often distributed across multiple entities like stores, regions, or departments. To make meaningful decisions, we need to aggregate and compare trends over time, rather than looking at isolated records.

 

In this tutorial, we’ll learn how to create a multi-line time series chart in Apache Superset using a slightly more realistic dataset that includes multiple stores contributing to daily revenue and expenses.

 

Use Case: Revenue vs Expenses Across Multiple Stores

Imagine you are analyzing financial performance across different stores. Each store reports its daily revenue and expenses, and your goal is to understand:

 

·      Overall business performance over time

·      Whether revenue is consistently higher than expenses

·      Trends in profitability across days

 

Instead of analyzing each store separately, we’ll aggregate the data by date to get a unified view of performance.

 

store_revenue.csv

date,store_id,revenue,expenses
2026-04-01,S1,2000,1200
2026-04-01,S2,3000,2000
2026-04-02,S1,2500,1400
2026-04-02,S2,2700,1600
2026-04-03,S1,2200,1300
2026-04-03,S2,2600,1800
2026-04-04,S1,3000,1700
2026-04-04,S2,3000,1800
2026-04-05,S1,3200,1900
2026-04-05,S2,3000,1800
2026-04-06,S1,2800,1500
2026-04-06,S2,3000,1900
2026-04-07,S1,3500,2000
2026-04-07,S2,3000,2000
2026-04-08,S1,3600,2100
2026-04-08,S2,3200,2100
2026-04-09,S1,3400,2000
2026-04-09,S2,3100,1900
2026-04-10,S1,3700,2200
2026-04-10,S2,3300,2100
2026-04-11,S1,3900,2300
2026-04-11,S2,3500,2200
2026-04-12,S1,4000,2400
2026-04-12,S2,3600,2300
2026-04-13,S1,4200,2500
2026-04-13,S2,3700,2400
2026-04-14,S1,4100,2400
2026-04-14,S2,3600,2300
2026-04-15,S1,4300,2600
2026-04-15,S2,3800,2500
2026-04-16,S1,4400,2700
2026-04-16,S2,3900,2600
2026-04-17,S1,4500,2800
2026-04-17,S2,4000,2700
2026-04-18,S1,4600,2900
2026-04-18,S2,4100,2800
2026-04-19,S1,4700,3000
2026-04-19,S2,4200,2900
2026-04-20,S1,4800,3100
2026-04-20,S2,4300,3000
2026-04-21,S1,4900,3200
2026-04-21,S2,4400,3100
2026-04-22,S1,5000,3300
2026-04-22,S2,4500,3200
2026-04-23,S1,5100,3400
2026-04-23,S2,4600,3300
2026-04-24,S1,5200,3500
2026-04-24,S2,4700,3400
2026-04-25,S1,5300,3600
2026-04-25,S2,4800,3500
2026-04-26,S1,5400,3700
2026-04-26,S2,4900,3600
2026-04-27,S1,5500,3800
2026-04-27,S2,5000,3700
2026-04-28,S1,5600,3900
2026-04-28,S2,5100,3800
2026-04-29,S1,5700,4000
2026-04-29,S2,5200,3900
2026-04-30,S1,5800,4100
2026-04-30,S2,5300,4000
2026-05-01,S1,6000,4200
2026-05-01,S2,5500,4100
2026-05-02,S1,6100,4300
2026-05-02,S2,5600,4200
2026-05-03,S1,6200,4400
2026-05-03,S2,5700,4300
2026-05-04,S1,6300,4500
2026-05-04,S2,5800,4400
2026-05-05,S1,6400,4600
2026-05-05,S2,5900,4500
2026-05-06,S1,6500,4700
2026-05-06,S2,6000,4600
2026-05-07,S1,6600,4800
2026-05-07,S2,6100,4700
2026-05-08,S1,6700,4900
2026-05-08,S2,6200,4800
2026-05-09,S1,6800,5000
2026-05-09,S2,6300,4900
2026-05-10,S1,7000,5200
2026-05-10,S2,6500,5100
2026-05-11,S1,7100,5300
2026-05-11,S2,6600,5200
2026-05-12,S1,7200,5400
2026-05-12,S2,6700,5300
2026-05-13,S1,7300,5500
2026-05-13,S2,6800,5400
2026-05-14,S1,7400,5600
2026-05-14,S2,6900,5500
2026-05-15,S1,7500,5700
2026-05-15,S2,7000,5600
2026-05-16,S1,7600,5800
2026-05-16,S2,7100,5700
2026-05-17,S1,7700,5900
2026-05-17,S2,7200,5800
2026-05-18,S1,7800,6000
2026-05-18,S2,7300,5900
2026-05-19,S1,7900,6100
2026-05-19,S2,7400,6000
2026-05-20,S1,8000,6200
2026-05-20,S2,7500,6100

   

Follow below step-by-step procedure to build a Multi-line chart.

 

Step 1: Upload store_revenue.csv file to Superset.

 

Data -> Upload CSV to database

 

·      Upload store_revenue.csv file

·      Specify database and schema where you want to upload the csv file

·      Give table name as store_revenue

 

   

Expand Columns section.

·      Select all the columns to columns to read section

·      Set Column data types to {"date": "datetime64[ns]", "store_id": "string", "revenue" : "float32", "expenses" : "float32"}

 

Click on Upload button to upload the csv file to store_revenue table.

 

Navigate to Datasets listing page, you can able to see the store_revenue dataset.

 

Step 2: Create Multi line chart.

 

Click on store_revenue dataset, you will be taken to chart configuration page.

 

Click on the link ‘view all charts’.

 

Select Line Chart.

 

Click on Select button. You will be taken to line chart configuration page.

 

Drag and drop date column to X-axis

Drag and drop revenue column to Metrics section and choose aggregate as SUM.

 

Drag and drop expenses column to Metrics section and choose aggregate as SUM.

 

Click on ‘Create chart’ button to draw the chart.

 

Save the chart. That’s it, you're good to go.

 

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