spiketools.stats.anova.create_dataframe_bins¶
- spiketools.stats.anova.create_dataframe_bins(bin_data, other_data=None, dropna=True, dtypes=None, bin_columns=None)[source]¶
Create a dataframe from an array of binned data.
- Parameters:
- bin_data2d or 3d array
An array of data organized into pre-computed bins. If a 2d array, should be organized as [n_trials, n_bins]. If a 3d array, should be organized as [n_trials, n_xbins, n_ybins].
- other_datadict, optional
Additional data columns, reflecting data per trial, to add to the dataframe. Each key should be a column label and each value should be an array of length n_trials.
- dropnabool, optional, default: True
Whether to drop NaN values from the dataframe.
- dtypesdict, optional
Data types to typecast columns to. Each key should be a column label, and each associated value the type to typecast to.
- bin_columnslist of str, optional
Custom column labels for the bin data. If not provided, defaults to [‘bin’, ‘fr’] for 1d or [‘xbin’, ‘ybin’ ‘fr’] for 2d bins.
- Returns:
- dfpd.DataFrame
Constructed dataframe.
Examples
Create a dataframe from arrays representing 3 trials of firing rate across 5 spatial bins:
>>> data = np.array([[1, 2, 3, 7, 2], [4, 5, 6, 4, 1], [8, 9, 10, 9, 8]]) >>> df = create_dataframe_bins(data)