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This package is used to calculate the gradients of a shifted column of dataset to form a rows
column_0 column_1 column_2 column_3 column_4 column_5
0 0.05601 NaN NaN NaN NaN NaN
1 0.08611 0.05601 NaN NaN NaN NaN
2 0.05125 0.08611 0.05601 NaN NaN NaN
3 0.02576 0.05125 0.08611 0.05601 NaN NaN
4 0.01776 0.02576 0.05125 0.08611 0.05601 NaN
Once installed ns_gradient can be imported and functions called like so:
import pandas as pd
from ns_gradient.nsgrads import Nsgrads, calculator
df = pd.read_csv('./src/ns_gradient/all_sigs_df.csv')
df.drop(['Unnamed: 0'], axis=1, inplace=True)
result = calculator(dataset=df, periods=20, column='close')
print(result.get('gradients_mean')) # to get the mean
print(result.get('dataset')) # to retrieve data used to calculate the gradients
print(result.get('gradients')) # to get the vector gradients
FAQs
A package for calculating shifted gradients
We found that ns-gradient demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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