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
作者:不再依然07
这篇文章主要介绍了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,详细的内容需要的小伙伴可以参考一下下面文章内容
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 np import pandas as pd import matplotlib as mpl import matplotlib.pyplot as plt import seaborn as sns import warnings warnings.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 plot plt.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}) # Decorations plt.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:
2.绘制带误差阴影的时间序列图
实现功能:
python绘制带误差阴影的时间序列图。
实现代码:
from scipy.stats import sem import pandas as pd import matplotlib.pyplot as plt # Import Data df_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 Bands df_mean = df_raw.groupby('purchase_date').quantity.mean() df_se = df_raw.groupby('purchase_date').quantity.apply(sem).mul(1.96) # Plot plt.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 borders plt.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 limits s, e = plt.gca().get_xlim() plt.xlim(s, e - 2) plt.ylim(4, 10) # Draw Horizontal Tick lines for 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:
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 pd import numpy as np import matplotlib.pyplot as plt # Import Data df = 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-axis ax2.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:
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 pd import matplotlib.pyplot as plt import seaborn as sns # Read data df = pd.read_csv("D:\数据杂坛\datasets\email_campaign_funnel.csv") # Draw Plot plt.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=df.loc[df[group_col] == group, :], order=order_of_bars, color=c, label=group) # Decorations plt.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:
到此这篇关于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+绘制金字塔图的文章就介绍到这了,更多相关Python图绘制内容请搜索脚本之家以前的文章或继续浏览下面的相关文章希望大家以后多多支持脚本之家!