Generate Fake Data

Sometimes you need some realistic looking data. This can be useful when testing an app or design. This could also be useful for showing examples such as test API endpoints or. You can also use this data to test data visualizations.

Example Sales Data

Create a table of mock sales data for a retail shoe company
Sure! Here's a table of mock sales data for a retail shoe company:
Date Product Quantity Sold Price per Unit Total Sales
2023-01-01 Sneakers 50 $50 $2,500
2023-01-02 Sandals 30 $30 $900
2023-01-03 Boots 20 $80 $1,600
2023-01-04 Heels 40 $60 $2,400
2023-01-05 Sneakers 25 $50 $1,250
2023-01-06 Loafers 15 $70 $1,050
2023-01-07 Sandals 35 $30 $1,050
2023-01-08 Sneakers 45 $50 $2,250
2023-01-09 Boots 20 $80 $1,600

We can change the output format as well. I typically use JSON for software I'm writing and csv when I want to import the data into excel.

csv

Format the table as csv. Make sure to escape any special characters.
Here's the table formatted as a CSV file with special characters escaped:

Date,Product,Quantity Sold,Price per Unit,Total Sales
2023-01-01,Sneakers,50,"$50","$2,500"
2023-01-02,Sandals,30,"$30","$900"
2023-01-03,Boots,20,"$80","$1,600"
2023-01-04,Heels,40,"$60","$2,400"
2023-01-05,Sneakers,25,"$50","$1,250"
2023-01-06,Loafers,15,"$70","$1,050"
2023-01-07,Sandals,35,"$30","$1,050"
2023-01-08,Sneakers,45,"$50","$2,250"
2023-01-09,Boots,20,"$80","$1,600"
2023-01-10,Heels,30,"$60","$1,800"
2023-01-11,Sneakers,40,"$50","$2,000"
2023-01-12,Loafers,20,"$70","$1,400"
2023-01-13,Sandals,25,"$30","$750"
2023-01-14,Sneakers,35,"$50","$1,750"
2023-01-15,Boots,15,"$80","$1,200"
2023-01-16,Heels,25,"$60","$1,500"
2023-01-17,Sneakers,30,"$50","$1,500"
2023-01-18,Loafers,10,"$70","$700"
2023-01-19,Sandals,20,"$30","$600"
2023-01-20,Boots,40,"$80","$3,200"

JSON

Now JSON
[
  {
    "Date": "2023-01-01",
    "Product": "Sneakers",
    "Quantity Sold": 50,
    "Price per Unit": "$50",
    "Total Sales": "$2,500"
  },
  {
    "Date": "2023-01-02",
    "Product": "Sandals",
    "Quantity Sold": 30,
    "Price per Unit": "$30",
    "Total Sales": "$900"
  },
  {
    "Date": "2023-01-03",
    "Product": "Boots",
    "Quantity Sold": 20,
    "Price per Unit": "$80",
    "Total Sales": "$1,600"
  },
  {
    "Date": "2023-01-04",
    "Product": "Heels",
    "Quantity Sold": 40,
    "Price per Unit": "$60",
    "Total Sales": "$2,400"
  },
  {
    "Date": "2023-01-05",
    "Product": "Sneakers",
    "Quantity Sold": 25,
    "Price per Unit": "$50",
    "Total Sales": "$1,250"
  },
  {
    "Date": "2023-01-06",
    "Product": "Loafers",
    "Quantity Sold": 15,
    "Price per Unit": "$70",
    "Total Sales": "$1,050"
  },
  {
    "Date": "2023-01-07",
    "Product": "Sandals",
    "Quantity Sold": 35,
    "Price per Unit": "$30",
    "Total Sales": "$1,050"
  },
  ...
]

Example Weather Data

We can ask for specific columns as well.

Create a table of mock daily weather data. Include columns for temperature, humidity, precipitation, and other important weather data.
Sure! Here's a table of mock daily weather data for a specific location:
Date Temperature (°C) Humidity (%) Precipitation (mm) Wind Speed (km/h) Cloud Cover
2023-05-01 15 70 0.0 10 30%
2023-05-02 18 65 0.0 12 20%
2023-05-03 21 60 0.0 15 10%
2023-05-04 24 55 0.0 18 5%
2023-05-05 26 50 0.0 20 5%
2023-05-06 28 45 0.0 22 5%
2023-05-07 30 40 0.0 25 5%
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