dataframes 1.0.2
Simple DataFrame for D programming language
To use this package, run the following command in your project's root directory:
Manual usage
Put the following dependency into your project's dependences section:
DataFrame
Simple DataFrame for D programming language. Each field from the given struct will be converted as DataFrame Column to store the array. This library is focused on making a easy to use DataFrame in D.
Install
Add dataframes
to your project by running the following command.
dub add dataframes
Create a new DataFrame
Create a struct that represents the Row of the DataFrame. For example, to store the item and price information.
struct Item
{
string name;
double unitPrice;
int quantity;
}
With this library, we can't add more columns to DataFrame in runtime. So include the additional fields to the above struct if required. Example,
struct Item
{
string name;
double unitPrice;
int quantity;
double totalPrice;
}
Now create the DataFrame.
auto df = new DataFrame!Item;
Adding items
To add initial data, initialize the DataFrame as,
auto df = new DataFrame!Item(
name: ["Pencil", "Pen", "Notebook"],
unitPrice: [5.0, 10.0, 25.0],
quantity: [5, 2, 7]
);
To add items one by one,
df.add(Item("Pen", 10.0, 1));
// OR from the list of Items
foreach(item; items)
df.add(item)
Preview the DataFrame data
Print the DataFrame to see the content. If the DataFrame has less than or equal to 10 rows then it prints the full DataFrame. It prints only first 5 and the last 5 rows otherwise.
Example:
df.writeln;
Sample output:
name unitPrice quantity totalPrice
Pencil 5.00 5 nan
Pen 10.00 2 nan
Notebook 25.00 7 nan
3 rows
Full Example
import std.stdio;
import dataframes;
struct Item
{
string name;
double unitPrice;
int quantity;
double totalPrice;
}
void main()
{
auto df = new DataFrame!Item(
name: ["Pencil", "Pen", "Notebook"],
unitPrice: [5.0, 10.0, 25.0],
quantity: [5, 2, 7]
);
// Preview
df.writeln;
}
Number of Columns and Rows
writeln("Columns: ", df.ncol);
writeln("Rows : ", df.nrow); // OR `df.length`
Column names
writeln(df.columnNames);
Access Rows and Columns
Access rows by index.
auto firstRow = df.row(0);
writeln(firstRow.name, " ", firstRow.unitPrice * firstRow.quantity);
Access column,
auto firstPrice = df.unitPrice[0];
Updating the derived columns
In the above example, totalPrice
data is not available in the initial dataset. To calculate the totalPrice
,
df.totalPrice = df.unitPrice * df.quantity;
Above command will update totalPrice
of all the rows.
For complex formula or business logic, use the temporary column to calculate the total price and add the results to DataFrame.
Column!double discounts;
foreach(name; df.name)
{
if (name == "Notebook")
discounts ~= 0.05;
else if (name == "Pen")
discounts ~= 0.02;
else
discounts ~= 0;
}
df.totalPrice = (df.unitPrice - discounts) * df.quantity;
Using std.algorithm
goodies with the DataFrame
Following example shows the sum of total prices of a few selected items.
df.rows
.filter!(item => item.name == "Pencil" || item.name == "Pen")
.map!(item => item.totalPrice)
.sum
.writeln;
Multisort using name and quantity fields.
df.rows
.multiSort!("a.name < b.name", "a.quantity > b.quantity")
.writeln;
Importing data from CSV file
If struct fields and data in CSV matches then we can give csvReader!Item
to import all the items. But the CSV file may contain more data which are not imported. In such cases, define a new Tuple type.
import std.csv;
import std.typecons;
// name unitPrice quantity
alias ItemCsvData = Tuple!(string, double, int);
auto df = new DataFrame!Item;
auto file = File("items_2024_10_26.csv", "r");
// header: null to ignore the header row
foreach (record;file.byLine.joiner("\n").csvReader!ItemCsvData(header: null))
df.add(Item(record[0], record[1], record[2]));
// Preview the imported data
df.writeln;
Copying the DataFrame or creating DataFrame of new Type
To create a PriceList
dataframe from the list of items.
struct PriceList
{
string name;
double price;
}
df.rows
.sort!("a.name < b.name")
.uniq!("a.name == b.name")
.to_df!PriceList
.writeln;
- Registered by Aravinda VK
- 1.0.2 released 2 months ago
- aravindavk/dataframes-d
- MIT
- Copyright © 2024, Aravinda VK <[email protected]>
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- none
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