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This article mainly explains "how to draw Pareto map with Python". Interested friends may wish to have a look. The method introduced in this paper is simple, fast and practical. Let's let the editor take you to learn how to draw a Pareto map with Python.

# Random colors, from fakerdef rand_color ()-> str: return random.choice (["# c23531", "# 2f4554", "# 61a0a8", "# d48265", "# 749f83", "# ca8622", "# bda29a", "# 6e7074", "# 546570") "# c4ccd3", "# f05b72", "# 444693", "# 726930", "# b2d235", "# 6d8346", "# ac6767", "# 1d953f", "# 6950a1",]) df_origin = pd.DataFrame ({'categories': ["vegetables", "fruits") "Pork", "e-commerce", "synthesis", "aquatic products"], 'sales': [random.randint (10,100) for _ in range (6)]}) print (df_origin) # in descending order of sales df_sorted = df_origin.sort_values (by='sales') Ascending=False) print (df_sorted) # Line chart x axis x_line_categories = [* range (7)] # Line chart y axis-downward cumulative frequency cum_percent = df_sorted ['sales'] .cumsum () / df_sorted [' sales'] .sum () * 100cum_percent = cum_percent.append (pd.Series ([0])) # add the starting frequency 0cum_percent = cum_percent.sort_values (ascending=True) print ( Df_sorted.categories.values.tolist () print (cum_percent.values.tolist ()) def pareto_bar ()-> Bar: line = (Line () .add _ xaxis (x_line_categories) .add _ yaxis (cumulative percentage) Cum_percent.values.tolist (), xaxis_index=1, yaxis_index=1, # use secondary y axis That is, extend_axis label_opts=opts.LabelOpts (is_show=False), is_smooth=True,)) bar = (Bar () .add _ xaxis (df_sorted.categories.values.tolist ()) .add _ yaxis ('sales', df_sorted.sales.values.tolist ()) in bar Category_gap=0) # .add _ yaxis ('percentage of total amount', cum_percent.values.tolist ()) .extend _ axis (xaxis=opts.AxisOpts (is_show=False, position='top')) .extend _ axis (yaxis=opts.AxisOpts (axistick_opts=opts.AxisTickOpts (is_inside=True), # scale facing inward axislabel_opts=opts.LabelOpts (formatter=' {value}%')) Position='right') .set _ series_opts (label_opts=opts.LabelOpts (is_show=True, font_size=14)) .set _ global_opts (title_opts=opts.TitleOpts (title=' Pareto example-sales\ n Make By tengyulong', subtitle=''), xaxis_opts=opts.AxisOpts (name=' item Type', type_='category') Yaxis_opts=opts.AxisOpts (axislabel_opts=opts.LabelOpts (formatter= "{value} pieces") bar.overlap (line) return barpareto_bar (). Render ('Pareto map .html') # or pareto_bar () .render_notebook ()

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