Thinking in Pandas by Hannah Stepanek

Author:Hannah Stepanek
Language: eng
Format: epub
ISBN: 9781484258392
Publisher: Apress

Listing 4-17Explicitly converting certain columns to datetime objects

Note Listing 4-17 assumes that there are no NaNs or placeholder values in the column. If there are, like in Listing 4-18, na_values must be specified to convert all the placeholder values to NaNs; otherwise, the column will be an object rather than a datetime because the placeholder values will be left as strings.>> data = io.StringIO(

"""

id,birth,height,weight

129237,04/10/1999,5.4,126

123083,unknown,6.1,150

123087,11/23/1989,4.5,111

"""

)

>> df = pd.read_csv(

data,

dtype={

'id': np.int32,

'height': np.float16,

'weight': np.int16},

parse_dates=["birth"],

na_values=["unknown"],

index_col=[0],

)

birth height weight

id

129237 1999-04-10 5.398438 26

123083 NaT 6.101562 150

123083 1989-11-23 6.101562 111

>> df.memory_usage(deep=True)

Index 24

birth 24

height 6

weight 6

>> df.dtypes

age int8

height float16

weight datetime64[ns]

>> df.index.dtype

dtype('int64')

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