Display multiindex dataframe as “sparsified” table #5370
Description
Problem
I'm always frustrated when I am trying to display the multiindex dataframe, but it is not readable
Solution
pandas when displaying a dataframe that have multiindex skips duplicate values to make the console output a bit easier on the eyes.
>>> import pandas as pd
>>> import numpy as np
>>>
>>> tuples = list(
... zip(
... *[
... ["bar", "bar", "baz", "baz", "foo", "foo", "qux", "qux"],
... ["one", "two", "one", "two", "one", "two", "one", "two"],
... ]
... )
... )
>>> index = pd.MultiIndex.from_tuples(tuples, names=["first", "second"])
>>> df = pd.DataFrame(np.random.randn(8, 2), index=index, columns=["A", "B"])
>>> df
A B
first second
bar one -0.883183 0.480221
two 0.861466 -0.659678
baz one -0.039308 0.116815
two 0.139792 0.787177
foo one 1.638924 -0.135970
two 0.408906 0.394975
qux one -0.467613 -0.239692
two 1.315613 0.867033I think it's worth the st.table command to work in a similar way. Currently the table is displayed as below:
As a workaround, we can render the table to HTML via pandas, but that's not perfect.
This is especially valuable for pivot tables.
>>> import pandas as pd
>>> import numpy as np
>>> df = pd.DataFrame(
... {
... "A": ["one", "one", "two", "three"] * 3,
... "B": ["A", "B", "C"] * 4,
... "C": ["foo", "foo", "foo", "bar", "bar", "bar"] * 2,
... "D": np.random.randn(12),
... "E": np.random.randn(12),
... }
... )
>>> pd.pivot_table(df, values="D", index=["A", "B"], columns=["C"])
C bar foo
A B
one A 0.590631 0.536188
B 0.933343 -0.708869
C 0.521529 0.377555
three A -0.665092 NaN
B NaN 1.060647
C -1.138812 NaN
two A NaN 0.500034
B 0.074022 NaN
C NaN 0.810322Additional context
MultiIndex / advanced indexing in pandas documentation
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