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數據可視化庫-Matplotlib基本操作

spa orm ott -- nds nth color pandas pri

python-3.7 pycharm  matplotlib 2.2.3

"""
    數據可視化庫-Matplotlib
    時間:2018\9\12 0012
"""
import numpy as np
import pandas as pd
import matplotlib  as mpl
import matplotlib.pyplot as plt

print("""\n----------------------------日期格式轉換-------------------------------------
--------------------------------------pd.to_datetime(Series)----------------------------------------\n
""") unrate = pd.read_csv("UNRATE.csv") unrate["DATE"] = pd.to_datetime(unrate[DATE]) print(unrate.head(12)) print("""\n----------------------------數據可視化庫------------------------------------- --------------------------------------matplotlib.pyplot(X軸,Y軸)----------------------------------------\n"""
) # plt.plot() # 畫圖操作 # plt.show() # 顯示出來 first_twelve = unrate[0:12] plt.plot(first_twelve[DATE], first_twelve[VALUE]) plt.xticks(rotation = 45) # X數字為45° plt.xlabel(Month) # X軸標簽 plt.ylabel(Unemployment Rate) # Y軸標簽 plt.title(Monthly Unemployment Trends 1948) # 標題 plt.show() print
("""\n----------------------------數據可視化庫------------------------------------- --------------------------------------plt.add_subplot(行數,列數,索引)----------------------------------------\n""") fig = plt.figure() # figuresize = (行,列) ax1 = fig.add_subplot(4, 3, 1) ax2 = fig.add_subplot(4, 3, 2) ax3 = fig.add_subplot(4, 3, 3) ax6 = fig.add_subplot(4, 3, 6) ax1.plot(np.random.randint(1, 5, 5), np.arange(5)) ax2.plot(np.arange(10) * 3, np.arange(10)) plt.show() print("""\n----------------------------數據可視化庫------------------------------------- --------------------------------------一幅圖畫多套數據----------------------------------------\n""") unrate[MONTH] = unrate[DATE].dt.month unrate[MONTH] = unrate[DATE].dt.month fig = plt.figure(figsize = (6, 3)) plt.plot(unrate[0:12][MONTH], unrate[0:12][VALUE], c = red) plt.plot(unrate[12:24][MONTH], unrate[12:24][VALUE], c = blue) plt.show() # fig = plt.figure(figsize = (10, 6)) colors = [red, blue, green, orange, black] for i in range(5): start_index = i * 12 end_index = (i + 1) * 12 subset = unrate[start_index:end_index] label = str(1948 + i) plt.plot(subset[MONTH], subset[VALUE], c = colors[i], label = label) plt.legend(loc = best) plt.xlabel(Month) # X軸標簽 plt.ylabel(Unemployment Rate) # Y軸標簽 plt.title(Monthly Unemployment Trends 1948-1952) # 標題 plt.show() print("""\n----------------------------數據可視化庫------------------------------------- --------------------------------------柱形圖ax.bar(位置,高度,寬度)----------------------------------------\n""") reviews = pd.read_csv(fandango_score_comparison.csv) cols = [FILM, RT_user_norm, Metacritic_norm, IMDB_norm, Fandango_Ratingvalue, Fandango_Stars] norm_reviews = reviews[cols] num_cols = [RT_user_norm, Metacritic_norm, IMDB_norm, Fandango_Ratingvalue, Fandango_Stars] bar_heights = norm_reviews.loc[0, num_cols].values # 第0行,第num_cols列 print(bar_heights) bar_prosions = np.arange(5) + 1 tick_prosions = range(1, 6) print(bar_prosions) ax = plt.subplot() ax.bar(bar_prosions, bar_heights, 0.3) # ax.barh(bar_prosions, bar_heights, 0.3) #縱橫轉換 ax.set_xticks(tick_prosions) ax.set_xticklabels(num_cols, rotation = 45) ax.set_xlabel("Rating Source") ax.set_ylabel("Average Rating") ax.set_title(Average User Rating For Averages: Age of Ultron(2015)) plt.show() print("""\n----------------------------數據可視化庫------------------------------------- --------------------------------------散點圖ax.scatter(x坐標,y坐標)----------------------------\n""") ax = plt.subplot() ax.scatter(norm_reviews[Fandango_Ratingvalue], norm_reviews[RT_user_norm]) ax.set_xlabel("Fandango") ax.set_ylabel("RottenTomatoes") plt.show() print("""\n----------------------------數據可視化庫------------------------------------- ---------------------------範圍的柱形圖ax.hist(數據,range(範圍低,範圍高),bins = 柱形圖範圍個數)--------------\n""") """ set_ylim(0,50)設置y軸區間 ax.boxplot(X,Y) 畫出四分圖 set_visible(False) 不顯示XY軸 """

運行結果:

技術分享圖片

技術分享圖片

技術分享圖片

技術分享圖片

技術分享圖片

技術分享圖片

數據可視化庫-Matplotlib基本操作