In [5]:
pd.read_csv(io.StringIO(t), converters={'date':pd.to_datetime}).info()
<class 'pandas.core.frame.DataFrame'>
Int64Index: 1 entries, 0 to 0
Data columns (total 4 columns):
int 1 non-null int64
float 1 non-null float64
date 1 non-null datetime64[ns]
str 1 non-null int64
dtypes: datetime64[ns](1), float64(1), int64(2)
memory usage: 40.0 bytes
In [6]:
pd.read_csv(io.StringIO(t), dtype={'int':'object'}, parse_dates=['date']).info()
<class 'pandas.core.frame.DataFrame'>
Int64Index: 1 entries, 0 to 0
Data columns (total 4 columns):
int 1 non-null object
float 1 non-null float64
date 1 non-null datetime64[ns]
str 1 non-null int64
dtypes: datetime64[ns](1), float64(1), int64(1), object(1)
memory usage: 40.0+ bytes
In [3]:
df = pd.read_csv(io.StringIO(t), dtype=object).info()
<class 'pandas.core.frame.DataFrame'>
Int64Index: 1 entries, 0 to 0
Data columns (total 4 columns):
int 1 non-null object
float 1 non-null object
date 1 non-null object
str 1 non-null object
dtypes: object(4)
memory usage: 40.0+ bytes