前段時間做Kaggle,在資料探索階段想將資料視覺化，但是發現python現有的畫相簿裡沒有相關的演算法實現，而R語言與JS只要兩行程式碼就能搞定了。。。本著探索精神，我就看了下R語言的實現程式碼，然後用python變相的實現了一下~

實驗資料：傳送門  

程式碼：

# author:OraYang
#import some lib
import numpy as np # linear algebra
import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)
import matplotlib.pyplot as plt
import seaborn as sns
color = sns.color_palette()

%matplotlib inline

pd.options.mode.chained_assignment = None  # default='warn'
products_df = pd.read_csv("../input/products.csv")
aisles_df = pd.read_csv("../input/aisles.csv")
departments_df = pd.read_csv("../input/departments.csv")
order_products_prior_df = pd.merge(products_df, aisles_df, on='aisle_id', how='left')
order_products_prior_df = pd.merge(order_products_prior_df, departments_df, on='department_id', how='left')
order_products_prior_df.head()
import matplotlib
import squarify
temp = order_products_prior_df[['product_name','aisle','department']]
temp = pd.concat([
    order_products_prior_df.groupby('department')['product_name'].nunique().rename('products_department'),
    order_products_prior_df.groupby('department')['aisle'].nunique().rename('aisle_department')
    ], axis=1).reset_index()
temp = temp.set_index('department')
temp2 = temp.sort_values(by="aisle_department", ascending=False)
# treemap parameters
x = 0.
y = 0.
width = 100.
height = 100.
cmap = matplotlib.cm.viridis

# color scale on the population
# min and max values without Pau
mini, maxi = temp2.products_department.min(), temp2.products_department.max()
norm = matplotlib.colors.Normalize(vmin=mini, vmax=maxi)
colors = [cmap(norm(value)) for value in temp2.products_department]
colors[1] = "#FBFCFE"
# labels for squares
labels = ["%s\n%d aisle num\n%d products num" % (label) for label in zip(temp2.index, temp2.aisle_department, temp2.products_department)]
# make plot
fig = plt.figure(figsize=(12, 10))
fig.suptitle("How are aisles organized within departments", fontsize=20)
ax = fig.add_subplot(111, aspect="equal")
ax = squarify.plot(temp2.aisle_department, color=colors, label=labels, ax=ax, alpha=.7)
ax.set_xticks([])
ax.set_yticks([])
# color bar
# create dummy invisible image with a color map
img = plt.imshow([temp2.products_department], cmap=cmap)
img.set_visible(False)
fig.colorbar(img, orientation="vertical", shrink=.96)

fig.text(.76, .9, "numbers of products", fontsize=14)
fig.text(.5, 0.1,
         "powered by OraYang \n aisle totale %d, products total : %d" % (temp2.aisle_department.sum(), temp2.products_department.sum()),
         fontsize=14,
         ha="center")
fig.text(.5, 0.07,
         "Source : http://blog.csdn.net/column/details/16605.html",
         fontsize=14,
         ha="center")
plt.show()