def style_index(data): styler = Styler(data.iloc[-1:], precision=2) def z_score(x): m = x.mean() return m - x.std() * 3, m + x.std() * 3 keys = [ "1D Perf.", "3M Perf.", "52W Perf.", "Rel. Volume", "1M RVol", "3M RVol" ] for key in keys: l, h = z_score(data[key]) styler = styler.background_gradient(cmap=CMAP, vmin=l, vmax=h, subset=[key]) keys = ['ATH Rank'] styler = styler.background_gradient(cmap=CMAP, vmin=-10, vmax=110, subset=keys) return styler
def style_spread(data): styler = Styler(data.iloc[-1:], precision=2) def z_score(x): m = x.mean() return m - x.std() * 3, m + x.std() * 3 keys = [ 'Mean', '6M Corr.', '3M Corr.', 'Carry', 'Implied Spread', 'RVol Spread' ] for key in keys: l, h = z_score(data[key]) styler = styler.background_gradient(cmap=CMAP, vmin=l, vmax=h, subset=[key]) keys = ['Rank', 'Pct. Rank'] styler = styler.background_gradient(cmap=CMAP, vmin=-10, vmax=110, subset=keys) styler = styler.background_gradient(cmap=CMAP, vmin=-3, vmax=3, subset=["Z-Score"]) return styler