python绘制发散型柱状图+误差阴影时间序列图+双坐标系时间序列图+绘制金字塔图 python绘制发散型柱状图+误差阴

1.绘制发散型柱状图
2.绘制带误差阴影的时间序列图
3.绘制双坐标系时间序列图
4.绘制金字塔图

1.绘制发散型柱状图 python绘制发散型柱状图，展示单个指标的变化的顺序和数量，在柱子上添加了数值文本。
实现代码：

import numpy as npimport pandas as pdimport matplotlib as mplimport matplotlib.pyplot as pltimport seaborn as snsimport warningswarnings.filterwarnings(action='once')df = pd.read_csv("C:\工作\学习\数据杂坛/datasets/mtcars.csv")x = df.loc[:, ['mpg']]df['mpg_z'] = (x - x.mean()) / x.std()df['colors'] = ['red' if x < 0 else 'green' for x in df['mpg_z']]df.sort_values('mpg_z', inplace=True)df.reset_index(inplace=True)# Draw plotplt.figure(figsize=(10, 6), dpi=80)plt.hlines(y=df.index,xmin=0,xmax=df.mpg_z,color=df.colors,alpha=0.8,linewidth=5)for x, y, tex in zip(df.mpg_z, df.index, df.mpg_z):t = plt.text(x, y, round(tex, 2), horizontalalignment='right' if x < 0 else 'left',verticalalignment='center', fontdict={'color':'black' if x < 0 else 'black', 'size':10})# Decorationsplt.gca().set(ylabel='$Model', xlabel='$Mileage')plt.yticks(df.index, df.cars, fontsize=12)plt.xticks(fontsize=12)plt.title('Diverging Bars of Car Mileage')plt.grid(linestyle='--', alpha=0.5)plt.show()

实现效果：

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2.绘制带误差阴影的时间序列图实现功能：
【python绘制发散型柱状图+误差阴影时间序列图+双坐标系时间序列图+绘制金字塔图】python绘制带误差阴影的时间序列图。
实现代码：

from scipy.stats import semimport pandas as pdimport matplotlib.pyplot as plt# Import Datadf_raw = pd.read_csv('F:\数据杂坛\datasets\orders_45d.csv',parse_dates=['purchase_time', 'purchase_date'])# Prepare Data: Daily Mean and SE Bandsdf_mean = df_raw.groupby('purchase_date').quantity.mean()df_se = df_raw.groupby('purchase_date').quantity.apply(sem).mul(1.96)# Plotplt.figure(figsize=(10, 6), dpi=80)plt.ylabel("Daily Orders", fontsize=12)x = [d.date().strftime('%Y-%m-%d') for d in df_mean.index]plt.plot(x, df_mean, color="#c72e29", lw=2)plt.fill_between(x, df_mean - df_se, df_mean + df_se, color="#f8f2e4")# Decorations# Lighten bordersplt.gca().spines["top"].set_alpha(0)plt.gca().spines["bottom"].set_alpha(1)plt.gca().spines["right"].set_alpha(0)plt.gca().spines["left"].set_alpha(1)plt.xticks(x[::6], [str(d) for d in x[::6]], fontsize=12)plt.title("Daily Order Quantity of Brazilian Retail with Error Bands (95% confidence)",fontsize=14)# Axis limitss, e = plt.gca().get_xlim()plt.xlim(s, e - 2)plt.ylim(4, 10)# Draw Horizontal Tick linesfor y in range(5, 10, 1):plt.hlines(y,xmin=s,xmax=e,colors='black',alpha=0.5,linestyles="--",lw=0.5)plt.show()

实现效果：

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3.绘制双坐标系时间序列图实现功能：
python绘制双坐标系（双变量）时间序列图。
实现代码：

import pandas as pdimport numpy as npimport matplotlib.pyplot as plt# Import Datadf = pd.read_csv("F:\数据杂坛\datasets\economics.csv")x = df['date']y1 = df['psavert']y2 = df['unemploy']# Plot Line1 (Left Y Axis)fig, ax1 = plt.subplots(1, 1, figsize=(12, 6), dpi=100)ax1.plot(x, y1, color='tab:red')# Plot Line2 (Right Y Axis)ax2 = ax1.twinx()# instantiate a second axes that shares the same x-axisax2.plot(x, y2, color='tab:blue')# Decorations# ax1 (left Y axis)ax1.set_xlabel('Year', fontsize=18)ax1.tick_params(axis='x', rotation=70, labelsize=12)ax1.set_ylabel('Personal Savings Rate', color='#dc2624', fontsize=16)ax1.tick_params(axis='y', rotation=0, labelcolor='#dc2624')ax1.grid(alpha=.4)# ax2 (right Y axis)ax2.set_ylabel("Unemployed (1000's)", color='#01a2d9', fontsize=16)ax2.tick_params(axis='y', labelcolor='#01a2d9')ax2.set_xticks(np.arange(0, len(x), 60))ax2.set_xticklabels(x [::60], rotation=90, fontdict={'fontsize': 10})ax2.set_title("Personal Savings Rate vs Unemployed: Plotting in Secondary Y Axis",fontsize=18)fig.tight_layout()plt.show()

实现效果：

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4.绘制金字塔图实现功能：
python绘制金字塔图，一种排过序的分组水平柱状图barplot，可很好展示不同分组之间的差异，可可视化逐级过滤或者漏斗的每个阶段。
实现代码：

import pandas as pdimport matplotlib.pyplot as pltimport seaborn as sns# Read datadf = pd.read_csv("D:\数据杂坛\datasets\email_campaign_funnel.csv")# Draw Plotplt.figure()group_col = 'Gender'order_of_bars = df.Stage.unique()[::-1]colors = [plt.cm.Set1(i / float(len(df[group_col].unique()) - 1))for i in range(len(df[group_col].unique()))]for c, group in zip(colors, df[group_col].unique()):sns.barplot(x='Users',y='Stage',data=https://www.it610.com/article/df.loc[df[group_col] == group, :],order=order_of_bars,color=c,label=group)# Decorationsplt.xlabel("$Users$")plt.ylabel("Stage of Purchase")plt.yticks(fontsize=12)plt.title("Population Pyramid of the Marketing Funnel", fontsize=18)plt.legend()plt.savefig('C:\工作\学习\数据杂坛\素材\\0815\金字塔', dpi=300, bbox_inches = 'tight')plt.show()

实现效果：