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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: here is a 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:

For c in col_list: if c.dtype = "Something"

list[]

List.append(c)?

1 Answer

0 votes
by (41.4k points)

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']}

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