If I have a dataframe with the following columns:
1. NAME object
2. On_Time object
3. On_Budget object
4. %actual_hr float64
5. Baseline Start Date datetime64[ns]
6. Forecast Start Date datetime64[ns]
I would like to be able to say: for this dataframe, give me a list of the columns which are of type 'object' or of type 'datetime'?
I have a function which converts numbers ('float64') to two decimal places, and I would like to use this list of dataframe columns, of a particular type, and run it through this function to convert them all to 2dp.
Maybe something like:
For c in col_list: if c.dtype = "Something"
list[]
List.append(c)?
If you want a list of columns of a certain type, you can use groupby:
>>> df = pd.DataFrame([[1, 2.3456, 'c', 'd', 78]], columns=list("ABCDE"))
>>> df
A B C D E
0 1 2.3456 c d 78
[1 rows x 5 columns]
>>> df.dtypes
A int64
B float64
C object
D object
E int64
dtype: object
>>> g = df.columns.to_series().groupby(df.dtypes).groups
>>> g
{dtype('int64'): ['A', 'E'], dtype('float64'): ['B'], dtype('O'): ['C', 'D']}
>>> {k.name: v for k, v in g.items()}
{'object': ['C', 'D'], 'int64': ['A', 'E'], 'float64': ['B']}