hkailee

# Loading pandas dataframe as anndata 
adata = qp.AnnData(df_fundamental_logreturn_minmax[ls_fundamental_target])

# Saving raw data for visualization later
adata.raw = adata

# log(x+1) transformation for all data
qp.pp.log1p(adata)

# Standardization scaling per feature

hkailee

import plotly.express as px

# grouping statistics
ds = df_all.groupby(['leiden', 'GICS Sector', 'GICS Sub-Industry'])['log_return_1mth'].count().reset_index()
ds.columns = ['leiden', 'GICS Sector', 'GICS Sub-Industry', 'count']

# plotting sunburst
fig = px.sunburst(
    ds, 
    path=[