piper.verbs.names¶
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piper.verbs.names(df: pandas.core.frame.DataFrame, regex: Optional[str] = None, astype: str = 'list') → Union[str, list, dict, pandas.core.series.Series, pandas.core.frame.DataFrame][source]¶ show dataframe column information
This function is useful reviewing or manipulating column(s)
The dictionary output is particularly useful when composing the rename of multiple columns.
Examples
import numpy as np import pandas as pd id_list = ['A', 'B', 'C', 'D', 'E'] s1 = pd.Series(np.random.choice(id_list, size=5), name='ids') region_list = ['East', 'West', 'North', 'South'] s2 = pd.Series(np.random.choice(region_list, size=5), name='regions') df = pd.concat([s1, s2], axis=1) names(df, 'list') ['ids', 'regions']
- Parameters
df – dataframe
regex – Default None. regular expression to ‘filter’ list of returned columns.
astype –
- Default ‘list’. See return options below:
’dict’ returns a dictionary object
’list’ returns a list object
’text’ returns columns joined into a text string
’series’ returns a pd.Series
’dataframe’ returns a pd.DataFrame
- Returns
- Return type
dictionary, list, str, pd.Series, pd.DataFrame