完整的代码如下: fromPILimportImagedefcreate_gif():# 创建图像列表images=[]# 生成图形并保存为单独的图片create_plots()# 载入图片foriinrange(3):img=Image.open('plots.png')images.append(img)# 保存成 GIFimages[0].save('animation.gif',save_all=True,append_images=images[1:],duration=1000,loop...
创建一个表 c.execute('''CREATE TABLE IF NOT EXISTS plots (id INTEGER PRIMARY KEY, plot BLOB)''') 保存图形到字节流 buf = io.BytesIO() plt.savefig(buf, format='png') buf.seek(0) 将图形插入到数据库 c.execute("INSERT INTO plots (plot) VALUES (?)", (buf.read(),)) conn.commit(...
import seaborn as sns import pandas as pd import numpy as np # Create a dataset df = pd.DataFrame(np.random.random((5,5)), columns=["a","b","c","d","e"]) # Default heatmap p1 = sns.heatmap(df) 使用Seaborn的heatmap()进行绘制,结果如下。 08. 相关性图 相关性图或相关矩阵...
Create your own GIF from your favourite anime Python Modules –Use pip install : pytube: Download Video (only if your source is from youtube) moviepy: For video editing Python Codes 1 2 3 4 5 6 7 8 9 10 11 from pytube import YouTube from moviepy.editor import * ## Download you...
Create your own GIF from your favourite anime Python Modules –Use pip install : pytube: Download Video (only if your source is from youtube) moviepy: For video editing Python Codes 1 2 3 4 5 6 7 8 9 10 11 from pytube import YouTube from moviepy.editor import * ## Download youtub...
#Createadataset df=pd.DataFrame(np.random.random((5,5)),columns=["a","b","c","d","e"]) #Defaultheatmap p1=sns.heatmap(df) 1. 2. 3. 4. 5. 6. 7. 8. 9. 使用Seaborn的heatmap()进行绘制,结果如下。 08. 相关性图
# -*- coding:utf-8 -*-fromstatsmodels.tsa.stattoolsimportadfullerimportpandasaspdimportmatplotlib.pyplotaspltimportnumpyasnpfromstatsmodels.graphics.tsaplotsimportplot_acf, plot_pacf# 移动平均图defdraw_trend(timeSeries, size): f = plt.figure(facecolor='white')# 对size个数据进行移动平均rol_mean =...
graphics library for the creation of GIF pictures, writtenby Thomas Boutell. gdmodule is an Python extension for thislibrary. It can do lines, arcs, fills, fonts and can also manipulateother GIF pictures. Included in the gdmodule is a graphing module,which can produce line plots from data....
#create figure fig, ax =plt.subplots(1) # Plot y1 vs x in blue on the left vertical axis. plt.xlabel("Date [AST]") plt.ylabel("Temperature [C]", color="b") plt.tick_params(axis="y", labelcolor="b") plt.plot(DAT, tem, "b-", linewidth=1) ...
createpatches.Source: http://matplotlib.org/dev/users/annotations_guide.html#zoom-effect-between-axes"""trans1=blended_transform_factory(ax1.transData,ax1.transAxes)trans2=blended_transform_factory(ax2.transData,ax2.transAxes)bbox=Bbox.from_extents(xmin,0,xmax,1)mybbox1=TransformedBbox(bbox...