一、顏色

二、實例

#讀者分布
import pandas as pd
import matplotlib.pyplot as plt
def age_pie():
plt.rcParams["font.family"] = "SimHei"
df = pd.read_csv("user.csv", sep=";", header=None, names=["user_id", "location", "age"],
encoding="gbk")
# print(df.head())
df[(df.age == "41"")].index.tolist() # 找出不合法數值所在行
df = df.drop([1305]) # 刪除那一行
df[["age"]] = df[["age"]].astype(float)
labels = ["10-20", "20-30", "30-40", "40-50", "50-60"]
sizes = [len(df[(df.age >= 10) & (df.age < 20)]),
len(df[(df.age >= 20) & (df.age < 30)]),
len(df[(df.age >= 30) & (df.age < 40)]),
len(df[(df.age >= 40) & (df.age < 50)]),
len(df[(df.age >= 50) & (df.age < 60)])]
# print(sizes)
explode = (0, 0.05, 0, 0, 0) # 0.1為第二個元素凸出距離
colors = ["tomato", "lightskyblue", "goldenrod", "green", "y"]
# 餅圖繪製函數
plt.figure(figsize=(8, 6))
plt.pie(sizes, explode=explode, labels=labels, colors=colors,
autopct="%1.1f%%", shadow=False, pctdistance=0.8,
startangle=90, textprops={"fontsize": 16, "color": "w"})
plt.title("讀者年齡分布圖")
plt.axis("equal")
plt.legend(loc="upper right")
plt.savefig("age.png", dpi=600)
plt.show()
print(age_pie())
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三、代碼解析

3.1顯示正負號

import matplotlib.pyplot as plt
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#用來正常顯示負號
plt.rcParams["axes.unicode_minus"]=False
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3.2顯示中文

plt.rcParams["font.family"] = "SimHei"
黑體 SimHei
微軟雅黑 Microsoft YaHei
微軟正黑體 Microsoft JhengHei
新宋體 NSimSun
新細明體 PMingLiU
細明體 MingLiU
標楷體 DFKai-SB
仿宋 FangSong
楷體 KaiTi
仿宋_GB2312 FangSong_GB2312
楷體_GB2312 KaiTi_GB2312
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3.3找出不合法數據

import pandas as pd
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df[(df.age == "41"")].index.tolist()
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3.4刪除那一行

df = df.drop([1305])
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3.5顯示圖例

plt.legend(loc="upper right")
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3.6保存為圖片

plt.savefig("age.png", dpi=600)

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