How to Efficiently Convert a Python Dictionary to a Pandas DataFrame?

How to Convert Python Dict into a DataFrame

Context

Given a Python dictionary with keys as dates and values as corresponding values, one may need to convert this object into a pandas DataFrame with columns representing the dates and the values.

Direct Conversion

pd.DataFrame constructor expects multiple columns with data, but providing scalar values as in the case of a dictionary throws a ValueError.

Passing the dictionary's items (key-value pairs) directly to the constructor resolves this issue:

pd.DataFrame(d.items())  # or list(d.items()) in python 3

Efficient Conversion with pandas Series

A more efficient approach is to utilize the pd.Series constructor:

s = pd.Series(d, name='DateValue')

This creates a pandas Series with the values from the dictionary and a custom name. To add the dates as a column, set the index name to 'Date' and reset the index to obtain the desired DataFrame:

s.index.name = 'Date'
s.reset_index()

Conclusion

These methods provide efficient ways to convert a Python dictionary into a pandas DataFrame, allowing for easy data manipulation and analysis.

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