BiocGenerics 0.1.3

Generics for core data structures in biocpy

BiocGenerics

This package aims to provide common generics, much like R/Bioconductor. These generics allow users to operate on different objects is a consistent and reliable way.

Install

Install package from PyPI

pip install biocgenerics

Combine

Combine provide multiple functions to concatenate sequences and array-like objects.

• combine_seqs: Combine 1-dimensional sequences or vector-like objects.
• combine_rows: Combine n-dimensional or DataFrame like objects along the first dimension.
• combine_cols: Combine n-dimensional or DataFrame like objects along the second dimension.

from biocgenerics import combine_seqs, combine_rows

# example to combine multiple sequences
x = [1, 2, 3]
y = [0.1, 0.2]

print(combine_seqs(x, y))

# Works across types as well,
# e.g. sparse and dense matrices

num_cols = 20
x = np.ones(shape=(10, num_cols))
y = sp.identity(num_cols)

print(combine_rows(x, y))

Additionally, the combine generic, automatically dispatches to either combine_seqs or combine_cols methods depending on the inputs.

Set and Access names

Reliably access row and column names of Dataframe-like objects.

• rownames: Access row names of the object.
• set_rownames: Set new row names.
• colnames: Access column names.
• set_colnames: Set new column names.

import pandas as pd
from biocgenerics import rownames

df1 = pd.DataFrame([["a", 1], ["b", 2]], columns=["letter", "number"])

rownames(df1)

Check out the S4Vectors package for more information.

Note

This project has been set up using PyScaffold 4.4. For details and usage information on PyScaffold see https://pyscaffold.org/.