koala

Description:

koala

koala #





A poor man's version of a pandas DataFrame.
Collect, access & manipulate related data.
Examples #
Create a DataFrame from a csv file, preexisting column names and data, map
representations of the data or create an empty DataFrame and provide it with its
properties later on
final fromCsv = Dataframe.fromCsv(
path: 'path/to/file.csv',
eolToken: '\n',
maxRows: 40,
skipColumns: ['some-irrelevant-column'],
convertDates: true,
datePattern: 'dd-MM-yyyy'
);

final fromNamesAndData = DataFrame(
['a', 'b'],
[
[1, 2],
[3, 4],
[69, 420]
]
);
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The DataFrame class inherits from the list which contains its data matrix, so rows
may be accessed through normal indexing.
Columns on the other hand can be accessed by calling the instance with a contained column name.
// get a row
final secondRow = df[1];

// get a column
final bColumn = df('b');
final typedBColumn = df<double?>('b');
final slicedBColumn = df('b', start: 1, end: 5);
final filteredBColumn = df.columnAsIterable('b').where((el) => el > 7).toList();

// grab a singular record
final record = df.record<int>(3, 'b');
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Manipulate rows & column
// add and remove rows through the built-in list methods
df.add([2, 5]);
df.removeAt(4);
df.removeLast();

// manipulate columns
df.addColumn('newColumn', [4, 8, 2]);
df.removeColumn('newColumn');
df.transformColumn('a', (record) => record * 2);
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Copy or slice the DataFrame
final copy = df.copy();
final sliced = df.sliced(start: 30, end: 60);
df.slice(start: 10, end: 15); // in-place counterpart
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Sort the DataFrame in-place or get a sorted copy of it
final sorted = df.sortedBy('a', ascending: true, nullFirst: false);
sorted.sortBy('b', ascending: false, compareRecords: (a, b) => Comparable.compare(a.toString().length, b.toString().length));
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Obtain a readable representation of the DataFrame by simply passing it to the print function
DataFrame df = DataFrame.fromRowMaps([
{'col1': 1, 'col2': 2},
{'col1': 1, 'col2': 1},
{'col1': null, 'col2': 8},
]);
print(df);
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leads to the output:
col1 col2
0 | 1 2
1 | 1 1
2 | null 8
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...and so on and so forth.
Contribution #
I intend to actively maintain this repo, so feel free to create PRs, as there
still is a hell of a lot of functionality one may add to the DataFrame.
Acknowledgements #
This repository started off as a fork from the as of now unmaintained and generally lackluster df,
ultimately however, I wound up rewriting basically everything. Still, shout out boyz.
Author #
C'est moi, w2sv