Tree map
A treemap is a diagram that can be used to visualize numerical data with hierarchical categories. A typical example is a heat map of the Nikkei 225 or the S&P 500. This notebook uses squarify.
A treemap can also be created by using plotly.（ Treemap charts with Python - Plotly）
import numpy as np
import matplotlib.pyplot as plt
import japanize_matplotlib
import squarify
np.random.seed(0) # Fix random numbers
labels = ["A" * i for i in range(1, 5)]
sizes = [i * 10 for i in range(1, 5)]
colors = ["#%02x%02x%02x" % (i * 50, 0, 0) for i in range(1, 5)]
plt.figure(figsize=(5, 5))
squarify.plot(sizes, color=colors, label=labels)
plt.axis("off")
plt.show()
Visualize my portfolio
Suppose I have data on the acquisition price and current price for each stock I own. From there, I would create a heatmap like finviz.
Suppose we read the following data from csv.
※The data shown here are fictitious.
import pandas as pd
data = [
["PBR", 80.20, 130.00],
["GOOG", 1188.0, 1588.0],
["FLNG", 70.90, 230.00],
["ZIM", 400.22, 630.10],
["GOGL", 120.20, 90.90],
["3466\nラサールロジ", 156.20, 147.00], # 日本語表示のテスト用
]
df = pd.DataFrame(data)
df.columns = ["銘柄名", "取得価額", "現在の価額"]
df["評価損益"] = df["現在の価額"] - df["取得価額"]
df.head(6)
| 銘柄名 | 取得価額 | 現在の価額 | 評価損益 | |
|---|---|---|---|---|
| 0 | PBR | 80.20 | 130.0 | 49.80 |
| 1 | GOOG | 1188.00 | 1588.0 | 400.00 |
| 2 | FLNG | 70.90 | 230.0 | 159.10 |
| 3 | ZIM | 400.22 | 630.1 | 229.88 |
| 4 | GOGL | 120.20 | 90.9 | -29.30 |
| 5 | 3466\nラサールロジ | 156.20 | 147.0 | -9.20 |
Specify the color of the treemap.
Green for profitable areas and red for loss areas.
colors = []
percents = []
for p_or_l, oac in zip(df["評価損益"], df["取得価額"]):
percent = p_or_l / oac * 100
if p_or_l > 0:
g = np.min([percent * 255 / 100 + 100, 255.0])
color = "#%02x%02x%02x" % (0, int(g), 0)
colors.append(color)
else:
r = np.min([-percent * 255 / 100 + 100, 255])
color = "#%02x%02x%02x" % (int(r), 0, 0)
colors.append(color)
percents.append(percent)
print(df["銘柄名"].values)
print(colors)
print(percents)
['PBR' 'GOOG' 'FLNG' 'ZIM' 'GOGL' '3466\nラサールロジ']
['#00ff00', '#00b900', '#00ff00', '#00f600', '#a20000', '#730000']
[62.094763092269325, 33.670033670033675, 224.4005641748942, 57.43840887511868, -24.376039933444257, -5.8898847631241935]
Displaying a treemap
Let’s display the profit/loss in colors and the percentage of profit/loss on the treemap.
Japanese characters are not garbled because import japanize_matplotlib is used at the beginning.
current_prices = [cp for cp in df["現在の価額"]]
labels = [
f"{name}\n{np.round(percent, 2)}％".replace("-", "▼")
for name, percent in zip(df["銘柄名"], percents)
]
plt.figure(figsize=(10, 10))
plt.rcParams["font.size"] = 18
squarify.plot(current_prices, color=colors, label=labels)
plt.axis("off")
plt.show()
Add cache display to the treemap
Let’s also add a cache display to the treemap. The color should be gray.
plt.figure(figsize=(10, 10))
plt.rcParams["font.size"] = 18
squarify.plot(
current_prices + [3500], color=colors + ["#ccc"], label=labels + ["キャッシュ"]
)
plt.axis("off")
plt.show()
