TabularData framework lets you import, organize, and export a table of data. It’s great when you’re training a machine learning model but it’s a handy tool in many other scenarios as well. General: DevForums tag: TabularData TabularData framework documentation Explore and manipulate data in Swift with TabularData tech talk For a ‘hello world’ style example, see this DevForums post Share and Enjoy — Quinn “The Eskimo!” @ Developer Technical Support @ Apple let myEmail = "eskimo" + "1" + "@" + "apple.com"

Hello, I'm trying to figure out why an Int is being inferred over my explicit Double I'm parsing a CSV that contains 2 tables. I don't own the data so I'm not able to change it. The first row contains one cell that's used as a title for the document The second row is empty The third row contains one cell that's used as the header for the first table There is a header row for the table There's a dynamic number of rows for this table The an empty spacer row There is a row that's used as a title for the second table There is a header row for the table There's a dynamic number of rows for this table Im able to separate and create two DataFrame's from the data without issue. And this is the initializer I'm using. DataFrame( csvData: csvData, rows: rows, types: types, options: options ) Column names and their CSV types looks like this var types: [String: CSVType] { [ // ... "Column 38": .double, // ... ] } The data in the CSV is 0 nil nil nil 2 And this is what the one of the columns in question looks like when printed ▿ 38 : ┏━━━━━━━━━━━┓ ┃ Column 38 ┃ ┃ <Int> ┃ ┡━━━━━━━━━━━┩ │ 0 │ │ nil │ │ nil │ │ nil │ │ 2 │ └───────────┘ - name : "Column 38" - count : 5 ▿ contents : PackedOptionalsArray<Int> ▿ storage : <PackedOptionalsStorage<Int>: 0x600000206360> The docs state /// - types: A dictionary of column names and their CSV types. /// The data frame infers the types for column names that aren't in the dictionary. Since types contains the column name and it's still being inferred, my assumption is that the issue involves the renaming of the header row when it has empty cells occurs after the types are checked. Edit: After setting hasHeaderRow: false from true and adjusting my row offset, the types are now being assigned correctly. I'd recommend opening a feedback enhancement where renaming columns occurs before type assignment.

I'm importing a csv file of 299 rows and creating a subset by filtering on one column value (24 rows). I want to Chart just the filtered values. However, when I print one column I get values from the original dataFrame. Any suggestions? Thanks, David The code: import SwiftUI import Charts import TabularData struct DataPoint: Identifiable { var id = UUID() // This makes it conform to Identifiable var date: Date var value: Double } struct ContentView: View { @State private var dataPoints: [DataPoint] = [] var body: some View { Text("Hello") Chart { ForEach(dataPoints) { dataPoint in PointMark( x: .value("Date", dataPoint.date), y: .value("Value", dataPoint.value) ) } } .frame(height: 300) .padding() .onAppear(perform: loadData) } func loadData() { print("In Loading Data") // Load the CSV file if let url = Bundle.main.url(forResource: "observations", withExtension: "csv") { do { let options = CSVReadingOptions(hasHeaderRow: true, delimiter: ",") var data0 = try DataFrame(contentsOfCSVFile: url, options: options) let formattingOptions = FormattingOptions( maximumLineWidth: 200, maximumCellWidth: 15, maximumRowCount: 30 ) // print(data0.description(options: formattingOptions)) print("Number of Columns: \(data0.columns.count)") let columnsSet = ["plant_id", "date", "plot", "plantNumber", "plantCount"] data0 = try DataFrame(contentsOfCSVFile:url, columns: columnsSet, options: options) print("Number of Columns (after columnsSet): \(data0.columns.count)") print("Printing data0") print(data0.description(options: formattingOptions)) let data = data0.filter { $0["plant_id"] as? Int == 15 } print("Printing data") print(data.description(options: formattingOptions)) print(" Number of Rows \(data.rows.count)") for i in 0 ... data.rows.count { // print("\(i): \(data["plantCount"][i]!)") if let plantCount = data["plantCount"][i] as? Int { print("\(i): \(plantCount)") } else { print("\(i): Value not found or invalid type") } } // // var newDataPoints: [DataPoint] = [] // Here I plan to add the filtered data to DataPoint // DispatchQueue.main.async { dataPoints = newDataPoints } } catch { print("Error reading CSV file: \(error)") } } else { print("Didn't load csv file") } } } struct ContentView_Previews: PreviewProvider { static var previews: some View { ContentView() } } Here is the new dataFrame and print output Printing data ┏━━━━━┳━━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━┳━━━━━━━━━━━━━┳━━━━━━━━━━━━┓ ┃ ┃ plant_id ┃ date ┃ plot ┃ plantNumber ┃ plantCount ┃ ┃ ┃ <Int> ┃ <String> ┃ <Int> ┃ <Int> ┃ <Int> ┃ ┡━━━━━╇━━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━╇━━━━━━━━━━━━━╇━━━━━━━━━━━━┩ │ 0 │ 15 │ 2023-09-07 │ 1 │ 5 │ 5 │ │ 32 │ 15 │ 2023-09-07 │ 2 │ 10 │ 10 │ │ 38 │ 15 │ 2023-09-07 │ 2 │ 20 │ 20 │ │ 66 │ 15 │ 2023-09-07 │ 4 │ 25 │ 25 │ │ 77 │ 15 │ 2023-09-07 │ 5 │ 5 │ 5 │ │ 99 │ 15 │ 2023-09-14 │ 7 │ 45 │ 45 │ │ 142 │ 15 │ 2024-05-30 │ 1 │ 20 │ 20 │ │ 162 │ 15 │ 2024-05-30 │ 4 │ 5 │ 5 │ │ 169 │ 15 │ 2024-05-30 │ 5 │ 10 │ 10 │ │ 175 │ 15 │ 2024-05-30 │ 7 │ 10 │ 10 │ │ 188 │ 15 │ 2024-07-11 │ 1 │ 20 │ 40 │ │ 199 │ 15 │ 2024-07-11 │ 2 │ 5 │ 5 │ │ 215 │ 15 │ 2024-07-11 │ 5 │ 20 │ 30 │ │ 220 │ 15 │ 2024-07-11 │ 7 │ 30 │ 40 │ │ 236 │ 15 │ 2024-09-06 │ 1 │ 20 │ 60 │ │ 238 │ 15 │ 2024-09-06 │ 2 │ 30 │ 35 │ │ 248 │ 15 │ 2024-09-06 │ 5 │ 5 │ 35 │ │ 254 │ 15 │ 2024-09-06 │ 7 │ 50 │ 90 │ │ 267 │ 15 │ 2025-05-04 │ 1 │ 10 │ 70 │ │ 273 │ 15 │ 2025-05-04 │ 2 │ 10 │ 45 │ │ 282 │ 15 │ 2025-05-04 │ 5 │ 10 │ 45 │ │ 287 │ 15 │ 2025-05-04 │ 7 │ 30 │ 120 │ │ 292 │ 15 │ 2025-05-04 │ 8 │ 10 │ 0 │ │ 297 │ 15 │ 2925-05-04 │ 3 │ 10 │ 0 │ └─────┴──────────┴────────────┴───────┴─────────────┴────────────┘ 24 rows, 5 columns Number of Rows 24 0: 5 1: 80 2: 1 3: 1 4: 1 5: 3 6: 3 7: 1 8: 6 9: 1 10: 1 11: 1 12: 1 13: 10 14: 50 15: 1 16: 2 17: 1 18: 3 19: 8 20: 5 21: 3 22: 7 23: 2 24: 1