Convert pandas DataFrame to Other Format

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import pandas as pd

df = pd.DataFrame(
    {"col1": [1, 2], "col2": [0.5, 0.75]},
    index=["row1", "row2"],
    columns=["col1", "col2"],
)
df

[m for m in dir(df) if m.startswith("to_")]

['to_clipboard',
 'to_csv',
 'to_dict',
 'to_excel',
 'to_feather',
 'to_gbq',
 'to_hdf',
 'to_html',
 'to_json',
 'to_latex',
 'to_markdown',
 'to_numpy',
 'to_parquet',
 'to_period',
 'to_pickle',
 'to_records',
 'to_sql',
 'to_stata',
 'to_string',
 'to_timestamp',
 'to_xarray',
 'to_xml']

DataFrame.to_dict¶

df.to_dict()

{'col1': {'row1': 1, 'row2': 2}, 'col2': {'row1': 0.5, 'row2': 0.75}}

df.to_dict("list")

{'col1': [1, 2], 'col2': [0.5, 0.75]}

df.to_dict("series")

{'col1': row1    1
 row2    2
 Name: col1, dtype: int64,
 'col2': row1    0.50
 row2    0.75
 Name: col2, dtype: float64}

df.to_dict("split")

{'index': ['row1', 'row2'],
 'columns': ['col1', 'col2'],
 'data': [[1, 0.5], [2, 0.75]]}

df.to_dict("records")

[{'col1': 1, 'col2': 0.5}, {'col1': 2, 'col2': 0.75}]

df.to_dict("index")

{'row1': {'col1': 1, 'col2': 0.5}, 'row2': {'col1': 2, 'col2': 0.75}}

DataFrame.to_records¶

df.to_records()

rec.array([('row1', 1, 0.5 ), ('row2', 2, 0.75)],
          dtype=[('index', 'O'), ('col1', '<i8'), ('col2', '<f8')])

df.to_records(index=False)

rec.array([(1, 0.5 ), (2, 0.75)],
          dtype=[('col1', '<i8'), ('col2', '<f8')])