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https://github.com/adwaith-rajesh/ziframe
A minimal DataFrame library in zig
https://github.com/adwaith-rajesh/ziframe
dataframe zig ziglang
Last synced: about 1 month ago
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A minimal DataFrame library in zig
- Host: GitHub
- URL: https://github.com/adwaith-rajesh/ziframe
- Owner: Adwaith-Rajesh
- License: mit
- Created: 2024-06-15T11:18:27.000Z (5 months ago)
- Default Branch: master
- Last Pushed: 2024-06-17T17:10:55.000Z (5 months ago)
- Last Synced: 2024-10-02T07:04:43.203Z (about 1 month ago)
- Topics: dataframe, zig, ziglang
- Language: Zig
- Homepage:
- Size: 15.6 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Ziframe
A minimal 'DataFrame' library in zig.
In it's current form it can only perform basic operations such as
- add rows
- add columns
- read from CSV file
- removing rows/cols (using fromDF())
- apply a function over the DataFrame
- get shape
---
### Why
- It's part of something big.
- I wanted a way to read CSV files in zig in a proper way
---
### Usage
#### Building
- `build.zig.zon`
```zig
.{
...
.dependencies = .{
.ziframe = .{
.url = "https://github.com/Adwaith-Rajesh/ziframe/archive/refs/tags/v0.1.0.tar.gz",
.hash = "you know how to get this :)",
}
}
...
}
```
- `build.zig`
```zig
pub fn build(b: *std.Build) void {
...
const ziframe = b.dependency("ziframe", .{
.optimize = optimize,
.target = target,
});
const your_exe = b.addExecutable(.{
.name = "you_exe",
.root_source_file = b.path("path/to/source_file.zig"),
.target = target,
.optimize = optimize,
});
// add ziframe import
your_exe.root_module.addImport("ziframe", ziframe.module("ziframe"));
...
}
```
### Using Ziframe
- `test.csv`
```csv
id,marks1,marks2
1,10.23,20.45
2,12.90,33.45
3,46,50
```
- `main.zig`
```zig
const std = @import("std");
const debug = std.debug;
const zf = @import("ziframe");
pub fn main() !void {
var gpa = std.heap.GeneralPurposeAllocator(.{}){};
defer gpa.deinit()
const alloc = gpa.allocator();
// The columns of the DataFrame
const DFColumns = struct {
id: u32,
marks1: f64,
marks2: f64,
};
// Create an empty DataFrame
// var df = zf.DataFrame(Columns).init(alloc);
// defer df.deinit();
// read test.csv a create a new DataFrame
var df = try zf.DataFrame(DFColumns).fromCSV(alloc, "./test.csv", .{});
defer df.deinit();
debug.print("CSV file contents\n", .{});
debug.print("{}\n", .{df});
// adding a new row
try df.append(.{ .id = 4, .marks1 = 10, .marks2 = 20 });
debug.print("Add new row\n", .{});
debug.print("{}\n", .{df});
// Create a new DF with id and total marks from 'df'
const TotalDFCols = struct {
id: u32,
total: f64,
};
// function on how to create the new df
const total = struct {
fn in(row: DFColumns) ?TotalDFCols {
return .{
.id = row.id,
.total = row.marks1 + row.marks2,
};
}
}.in;
var total_df = try zf.DataFrame(TotalDFCols).fromDF(alloc, DFColumns, df, total);
defer total_df.deinit();
debug.print("New DataFrame with the total columns\n", .{});
debug.print("{}\n", .{total_df});
// filtering
// filter DataFrame, display only even ids
const filterEven = struct {
fn in(row: TotalDFCols) ?TotalDFCols {
if (row.id % 2 != 0) return null;
return row;
}
}.in;
var even_df = try zf.DataFrame(TotalDFCols).fromDF(alloc, TotalDFCols, total_df, filterEven);
defer even_df.deinit();
debug.print("DataFrame with only even ids\n", .{});
debug.print("{}\n", .{even_df});
// printing the shape and size
debug.print("shape of df: {} size of df: {}\n", .{ df.shape(), df.shape().size() });
debug.print("shape of total_df: {} size of df: {}\n", .{ total_df.shape(), total_df.shape().size() });
debug.print("shape of even_df: {} size of df: {}\n", .{ even_df.shape(), even_df.shape().size() });
// Map Function
// set total = 50 where id = 2
const update = struct {
// pointer to the row
pub fn in(row: *TotalDFCols) !void {
if (row.*.id == 2) {
row.*.total = 50;
}
}
}.in;
try even_df.map(update);
debug.print("\nset total = 50 where id = 2\n", .{});
debug.print("{}\n", .{even_df});
}
```
- output
Output
```commandline
CSV file contents
index id marks1 marks2
0 1 10.2300000 20.4500000
1 2 12.9000000 33.4500000
2 3 46.0000000 50.0000000
Add new row
index id marks1 marks2
0 1 10.2300000 20.4500000
1 2 12.9000000 33.4500000
2 3 46.0000000 50.0000000
3 4 10.0000000 20.0000000
New DataFrame with the total columns
index id total
0 1 30.6800000
1 2 46.3500000
2 3 96.0000000
3 4 30.0000000
DataFrame with only even ids
index id total
0 2 46.3500000
1 4 30.0000000
shape of df: 4x3 size of df: 12
shape of total_df: 4x2 size of df: 8
shape of even_df: 2x2 size of df: 4
set total = 50 where id = 2
index id total
0 2 50.0000000
1 4 30.0000000
```
---
### More docs in the future - maybe :)
### Bye..