Extensions of pythonnet package to support pandas DataFrame conversions
Project description
pandasnet
pandasnet
si a python package build on top of pythonnet
.
It provides additional data conversions for pandas
, numpy
and datetime
Prerequisites
- python 3.6 or higher
- dotnet
Installation
pip install pandasnet
Features
To load the converter you need to import the pacakge once in your python environment. If the dotnet clr isn't started yet through the pytonnet package the import will.
import pandasnet
Below you can found an exhausitve list of supported data convertions.
Python -> .Net
Python | .Net |
---|---|
datetime.datetime | DateTime |
datetime.date | DateTime |
datetime.timedelta | TimeSpan |
datetime.time | TimeSpan |
numpy.ndarray(dtype=bool_) | bool[] |
numpy.ndarray(dtype=int8) | sbyte[] |
numpy.ndarray(dtype=int16) | short[] |
numpy.ndarray(dtype=int32) | int[] |
numpy.ndarray(dtype=int64) | long[] |
numpy.ndarray(dtype=uint8) | byte[] |
numpy.ndarray(dtype=uint16) | ushort[] |
numpy.ndarray(dtype=uint32) | uint[] |
numpy.ndarray(dtype=uint64) | ulong[] |
numpy.ndarray(dtype=float32) | float[] |
numpy.ndarray(dtype=float64) | double[] |
numpy.ndarray(dtype=datetime64) | DateTime[] |
numpy.ndarray(dtype=timedelta64) | TimeSpan[] |
numpy.ndarray(dtype=str) | string[] |
pandas._libs.tslibs.timestamps.Timestamp | DateTime |
pandas._libs.tslibs.timedeltas.TimeDelta | TimeSpan |
pandas.core.series.Series | Array |
pandas.core.frame.DataFrame | Dictionary[string, Array] |
.Net -> Python
.Net | Python |
---|---|
DateTime | datetime.datetime |
TimeSpan | datetime.timedelta |
bool[] | numpy.ndarray(dtype=bool_) |
sbyte[] | numpy.ndarray(dtype=int8) |
short[] | numpy.ndarray(dtype=int16) |
int[] | numpy.ndarray(dtype=int32) |
long[] | numpy.ndarray(dtype=int64) |
byte[] | numpy.ndarray(dtype=uint8) |
ushort[] | numpy.ndarray(dtype=uint16) |
uint[] | numpy.ndarray(dtype=uint32) |
ulong[] | numpy.ndarray(dtype=uint64) |
float[] | numpy.ndarray(dtype=float32) |
double[] | numpy.ndarray(dtype=float64) |
DateTime[] | numpy.ndarray(dtype=datetime64) |
TimeSpan[] | numpy.ndarray(dtype=timedelta64) |
Dictionary[string, Array] | pandas.core.frame.DataFrame |
Project details
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