Module pandas_compat 

Pandas DataFrame and Series integration

This module provides utilities for converting between pandas DataFrames/Series and scirs2 data structures with zero-copy where possible.

Example (Python)

import pandas as pd
import scirs2
import numpy as np

# Create pandas Series
s = pd.Series([1.0, 2.0, 3.0, 4.0, 5.0])

# Convert to TimeSeries
ts = scirs2.pandas_to_timeseries(s)

# Perform operations
arima = scirs2.PyARIMA(1, 1, 0)
arima.fit(ts)
forecast = arima.forecast(5)

# Convert back to pandas
forecast_series = pd.Series(forecast)

Functions

apply_along_axis

Apply a scirs2 function row-wise or column-wise to a DataFrame

apply_to_dataframe

Apply a scirs2 function to each column of a DataFrame

array_to_dataframe

Convert numpy array to pandas DataFrame

dataframe_to_array

Convert pandas DataFrame to numpy array (2D)

pandas_to_timeseries

Convert pandas Series to PyTimeSeries

register_pandas_module

Register pandas compatibility functions with Python module

rolling_apply

Rolling window operations on pandas Series with scirs2 functions

timeseries_to_pandas

Convert PyTimeSeries to pandas Series