`TypeError` if DataFrame contains duplicated column name (in some cases)

[saiwing-yeung]

This is kind of an edge case but the error message makes it somewhat difficult to identify the underlying issue.
If you have a Pandas DataFrame where there are duplicated column names and they are not integers, you'd get an exception when trying to plot something. MWE:

import io
df = pd.read_csv(io.StringIO("""
a, b, c, d
0, 1, 2, 2022-01-01
2, 3, 4, 2022-01-01
"""))
df.columns = ['a', 'b', 'c', 'c']
alt.Chart(df).mark_point().encode(x='a', y='b')

results in

TypeError: to_list_if_array() got an unexpected keyword argument 'convert_dtype'

Note that

• the duplicated columns are not used in plotting.
• if both duplicated columns are of type integer, then you would just get a warning. But with most other types (including floats) it would generate an exception.
• besides explicit renaming the columns like this, another scenario where you'd accidentally generate duplicated column names is calling toPandas() after join two PySpark DataFrames.

Using altair 4.2.0

Tracking

• ENH: Disallow duplicate column names everywhere by default pandas-dev/pandas#53217

[joelostblom]

My sense is that this issue should be handled by pandas and that it should not be possible to create a dataframe where two columns have the same name. Have you raised this on their issue tracker?

[JanetMatsen]

I think it would be nice to raise a more informative error. It came up for me too.

In my case, I had a big dataframe that causes some encoding errors if I dump the whole dataframe in. So I made a list of the subset of columns that I wanted to send to Altair. However, if this list is long or generated by complex logic, then it is easy to mistakenly include one column name twice.

A cartoon of my workflow was somewhat as follows, but I kept about 10 of 300 columns when I sent it to Altair and my list of ~10 had a duplicate.:

df = pd.DataFrame({'created_at':['2022-01-01', '2022-01-02', '2022-01-03', '2022-01-04', '2022-01-05']})
df["y"] = range(1, len(df)+1, 1)

keep_cols = ['created_at', 'created_at', 'y']  # <-- the logic that created this list led to a duplicate column name.

alt.Chart(df[keep_cols]).mark_circle(size=60).encode(
    x="created_at:T",
    y="y", 
)

[joelostblom]

Maybe we could introduce something like df.flags.allows_duplicate_labels = False (docs) in santize_dataframe which is where this error is raised, but I wonder why this isn't the default in pandas already so I opened pandas-dev/pandas#53217

[dangotbanned]

@MarcoGorelli is this resolved by adopting narwhals?

https://narwhals-dev.github.io/narwhals/pandas_like_concepts/column_names/

Duplicate column names are 🚫 banned 🚫.

Update

Yeah it is 🙂

import io
import pandas as pd
import altair as alt

df = pd.read_csv(
    io.StringIO("""
a, b, c, d
0, 1, 2, 2022-01-01
2, 3, 4, 2022-01-01
""")
)
df.columns = ["a", "b", "c", "c"]
alt.Chart(df).mark_point().encode(x="a", y="b")

File /site-packages/narwhals/_pandas_like/dataframe.py:106, in PandasLikeDataFrame._validate_columns(self, columns)
    [104]         msg += f"\n- '{key}' {value} times"
    [105] msg = f"Expected unique column names, got:{msg}"
--> [106] raise ValueError(msg)

ValueError: Expected unique column names, got:
- 'c' 2 times