Having life data failure and suspension points and using “reliability”, “matplotlib.pyplot” and “pandas” libraries I am able to generate distribution reliability model graphs using “Jupiter Notebook”:
Typical (sample) code structure:
import pandas as pd
import matplotlib.pyplot as plt
import reliability
from reliability.Fitters import Fit_Weibull_2P
from reliability.Probability_plotting import Weibull_probability_plot
file=(‘Failures and Suspensions.xlsx’)
df_fgq=pd.read_excel(file,sheet_name=‘FGQ’)
fgq_name=“FGQ”
data_fail_fgq=df_fgq[‘Life Parameter TF’][df_fgq[‘Failures vs Suspensions’]==1].tolist()
data_cens_fgq=df_fgq[‘Life Parameter TF’][df_fgq[‘Failures vs Suspensions’]==0].tolist()
fgq_r=Fit_Weibull_2P(failures=data_fail_fgq, right_censored=data_cens_fgq,
show_probability_plot=False,print_results=False,
CI=0.90,label=fgq_name)
plt.title(‘Reliability’)
plt.legend()
Is there a way to create such life data reliability analysis graphs using Dash/Plotly libraries?
If not, can they be converted to Dash environment, and if so, can they still be interactive?
Thank You