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Hi have a multiindex dataframe:
tuples = [('YTA_Q3', 1), ('YTA_Q3', 2), ('YTA_Q3', 3), ('YTA_Q3', 4), ('YTA_Q3', 99), ('YTA_Q3', 96)] # Index index = pd.MultiIndex.from_tuples(tuples, names=['Questions', 'Values']) # Columns columns = pd.MultiIndex.from_tuples([('YTA_Q3', '@')], names=['Questions', 'Values']) # Data data = [29.014949,5.0260590000000001, 6.6269119999999999, 1.3565260000000001, 41.632221999999999, 21.279499999999999] df1 = pd.DataFrame(data=data, index=index, columns=columns) How do I convert the inner values of the df's index to str?
My attempt:
df1.index.astype(str) returns a TypeError
344
To change the type of a DataFrame's index in Pandas, use the DataFrame. index. astype(~) method.
To revert the index of the dataframe from multi-index to a single index using the Pandas inbuilt function reset_index(). Returns: (Data Frame or None) DataFrame with the new index or None if inplace=True.
Pandas DataFrame: set_index() function The set_index() function is used to set the DataFrame index using existing columns. Set the DataFrame index (row labels) using one or more existing columns or arrays of the correct length. The index can replace the existing index or expand on it.
IIUC you need the last level of Multiindex. You could access it with levels:
df1.index.levels[-1].astype(str) In [584]: df1.index.levels[-1].astype(str) Out[584]: Index(['1', '2', '3', '4', '96', '99'], dtype='object', name='Values') EDIT
You could set your inner level with set_levels method of multiIndex:
idx = df1.index df1.index = df1.index.set_levels([idx.levels[:-1], idx.levels[-1].astype(str)]) If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
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