Dataframe class to support complex types in Genomics. The goal is to not compete with Pandas but will be inter-operable at some point.
Project description
BiocFrame
BiocFrame provides a base Dataframe class, intended to be a flexible data structure compared to Pandas DataFrame This would be interoperable with pandas but will support usecases in genomics.
Install
Package is published to PyPI
pip install biocframe
Usage
Lets create a DataFrame from a dictionary
from biocframe import DataFrame
df = DataFrame(
data = {
"seqnames": [
"chr1",
"chr2",
"chr2",
"chr2",
"chr1",
"chr1",
"chr3",
"chr3",
"chr3",
"chr3",
]
* 20,
"starts": range(100, 300),
"ends": range(110, 310),
"strand": ["-", "+", "+", "*", "*", "+", "+", "+", "-", "-"] * 20,
"score": range(0, 200),
"GC": [random() for _ in range(10)] * 20,
}
)
Access Properties
A couple of accessor methods/properties are available to access column names and dims
# find the dimensions
print(df.dims)
# get the column names
print(df.colnames)
Setters
Using the Pythonic way to set values
# set new column names
df.colnames = [... new colnames ...]
print(df.colnames)
# add or reassign columns
df["score"] = range(200, 400)
Slice the DataFrame
Currently slicing is only supported by indices. A future version may implement pandas query like operations.
sliced_df = df[3:7, 2:5]
For more use cases including subset, checkout the documentation
Note
This project has been set up using PyScaffold 4.3. For details and usage information on PyScaffold see https://pyscaffold.org/.
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