how to convert an empty pandas Dataframe into a polars Dataframe

Question

I have defined a pandas DataFrame as follows:

df_tmp = pd.DataFrame({'EDT': pd.Series(dtype='datetime64[ns]'),
                       'FSPB': pd.Series(dtype='str'),
                       'FS_LA': pd.Series(dtype='str'),
                       'lA': pd.Series(dtype='int'),
                       'avg': pd.Series(dtype='float64'),
                       'nw': pd.Series(dtype='float64')})

Is there any way to convert the above into an empty polars DataFrame?

memmy · Accepted Answer · 2022-08-09 18:59:46Z

3

According to the polars docs, polars DataFrames can take a pandas DataFrame in their constructor, so:

import pandas as pd
import polars as pl

df_tmp = pd.DataFrame({'EDT': pd.Series(dtype='datetime64[ns]'),
                       'FSPB': pd.Series(dtype='str'),
                       'FS_LA': pd.Series(dtype='str'),
                       'lA': pd.Series(dtype='int'),
                       'avg': pd.Series(dtype='float64'),
                       'nw': pd.Series(dtype='float64')})

df = pl.DataFrame(df_tmp)

should work.

answered Aug 9, 2022 at 18:59

memmy

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4 Comments

dubi Over a year ago

tried exactly this but it does not work. It somewhat looks like this cannot be created without data. But I need an EMPTY pl.DataFrame.

memmy Over a year ago

Interestingly enough, it seems to work for me. Running my code results in an empty polars dataframe (shaped 0,6) with the correct dtypes in each column. It's possible you're missing pyarrow, which is required for this? In any case, either my or ritchie's method above should both function, so try his answer as well.

ritchie46 Over a year ago

Yeap.. your function should work as well. OP might need to update polars and install pyarrow.

dubi Over a year ago

thank you all! A clean venv with reinstallation of polars and pyarrow did the job!

ritchie46 · Accepted Answer · 2022-08-09 19:04:10Z

import polars as pl
import pandas as pd

pandas_df = pd.DataFrame({'EDT': pd.Series(dtype='datetime64[ns]'),
                       'FSPB': pd.Series(dtype='str'),
                       'FS_LA': pd.Series(dtype='str'),
                       'lA': pd.Series(dtype='int'),
                       'avg': pd.Series(dtype='float64'),
                       'nw': pd.Series(dtype='float64')})

pl.from_pandas(pandas_df)

shape: (0, 6)
┌──────────────┬──────┬───────┬─────┬─────┬─────┐
│ EDT          ┆ FSPB ┆ FS_LA ┆ lA  ┆ avg ┆ nw  │
│ ---          ┆ ---  ┆ ---   ┆ --- ┆ --- ┆ --- │
│ datetime[ns] ┆ str  ┆ str   ┆ i64 ┆ f64 ┆ f64 │
╞══════════════╪══════╪═══════╪═════╪═════╪═════╡
└──────────────┴──────┴───────┴─────┴─────┴─────┘

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