Intersecting two pandas DataFrames

[KaparaNewbie]

The need for (or the convenience of) a function such as intersect_dfs is demonstrated in this StackExchange thread.
Often your workflow is pandas' based but at some point, during that process, you may want to intersect two data frames. Here intersect_dfs become useful as it takes two data frames as an input and returns their intersection as another data frame.

Given below are three tests for this function.

# preparations
import pandas as pd

df1 = pd.DataFrame({0: ['chr1', 'chr1', 'chr1', 'chr1', 'chr2'],
                    1: [1, 100, 150, 900, 1],
                    2: [100, 200, 500, 950, 100],
                    3: ['feature1', 'feature2', 'feature3', 'feature4', 'feature4'],
                    4: [0, 0, 0, 0, 0], 5: ['+', '+', '-', '+', '+'],
                    6: ["remember", "the", "5th", "of", "november"]})

df2 = pd.DataFrame({0: ['chr1', 'chr1'],
                    1: [155, 800],
                    2: [200, 901],
                    4: [0, 0],
                    5: ['-', '+']})

intersect_kwargs = {"s": True}
read_table_names = ["chrom", "start", "end", "name", "score", "strand", "whatever"]
other_read_table_kwargs = {"usecols": ["chrom", "start", "end"]}

# test 1
intersected_df = intersect_dfs(df1, df2,
                               intersect_kwargs=intersect_kwargs,
                               other_read_table_kwargs=other_read_table_kwargs,
                               read_table_names=read_table_names)

expected_df = pd.DataFrame({"chrom": ["chr1", "chr1"],
                            "start": [155, 900],
                            "end": [200, 901]})

assert intersected_df.equals(expected_df)

# test 2
intersected_df = intersect_dfs(df1, df2,
                               other_read_table_kwargs=other_read_table_kwargs)

expected_df = pd.DataFrame({"chrom": ["chr1", "chr1", "chr1"],
                            "start": [155, 155, 900],
                            "end": [200, 200, 901]})

assert intersected_df.equals(expected_df)

# test 3
intersected_df = intersect_dfs(df1, df2,
                               read_table_names=read_table_names)

expected_df = pd.DataFrame({"chrom": ["chr1", "chr1", "chr1"],
                            "start": [155, 155, 900],
                            "end": [200, 200, 901],
                            "name": ["feature2", "feature3", "feature4"],
                            "score": [0, 0, 0],
                            "strand": ["+", "-", "+"],
                            "whatever": ["the", "5th", "of"]})

assert intersected_df.equals(expected_df)