Drop `pandas` to `numpy` converter

marketstore
Tyler Goodlet 2022-03-29 13:15:23 -04:00
parent 1c6a46da5d
commit 94cba54beb
1 changed files with 1 additions and 57 deletions

View File

@ -22,8 +22,7 @@ from typing import Any
import decimal import decimal
import numpy as np import numpy as np
import pandas as pd from pydantic import BaseModel
from pydantic import BaseModel, validate_arguments
# from numba import from_dtype # from numba import from_dtype
@ -254,61 +253,6 @@ class Symbol(BaseModel):
return keys return keys
def from_df(
df: pd.DataFrame,
source=None,
default_tf=None
) -> np.recarray:
"""Convert OHLC formatted ``pandas.DataFrame`` to ``numpy.recarray``.
"""
df.reset_index(inplace=True)
# hackery to convert field names
date = 'Date'
if 'date' in df.columns:
date = 'date'
# convert to POSIX time
df[date] = [d.timestamp() for d in df[date]]
# try to rename from some camel case
columns = {
'Date': 'time',
'date': 'time',
'Open': 'open',
'High': 'high',
'Low': 'low',
'Close': 'close',
'Volume': 'volume',
# most feeds are providing this over sesssion anchored
'vwap': 'bar_wap',
# XXX: ib_insync calls this the "wap of the bar"
# but no clue what is actually is...
# https://github.com/pikers/piker/issues/119#issuecomment-729120988
'average': 'bar_wap',
}
df = df.rename(columns=columns)
for name in df.columns:
# if name not in base_ohlc_dtype.names[1:]:
if name not in base_ohlc_dtype.names:
del df[name]
# TODO: it turns out column access on recarrays is actually slower:
# https://jakevdp.github.io/PythonDataScienceHandbook/02.09-structured-data-numpy.html#RecordArrays:-Structured-Arrays-with-a-Twist
# it might make sense to make these structured arrays?
array = df.to_records(index=False)
_nan_to_closest_num(array)
return array
def _nan_to_closest_num(array: np.ndarray): def _nan_to_closest_num(array: np.ndarray):
"""Return interpolated values instead of NaN. """Return interpolated values instead of NaN.