The Python Graph Gallery displays hundreds of charts made with Python, always with explanation and reproduciible code
import plotly.graph_objs as go import numpy as np y0 = np.random.randn(50)-1 y1 = np.random.randn(50)+1 trace0 = go.Box( y=y0 ) trace1 = go.Box( y=y1 ) data = [trace0, trace1] plotly.offline.plot(data) Wind Rose Chart import plotly.graph_objs as go trace1 = go.Barp...
Interactive Data Analysis with FigureWidget ipywidgets Click Events Add Custom Controls Custom Buttons Sliders Dropdown Menus Range Slider and Selector Animations Intro to Animations Advanced Plot CSV Data Random Walk Peak Finding Smoothing LaTeX
import plotly.plotlyimport plotly.graph_objs as goimport numpy as npy0 = np.random.randn(50)-1y1 = np.random.randn(50)+1trace0 = go.Box(y=y0)trace1 = go.Box(y=y1)data = [trace0, trace1]plotly.offline.plot(data) Wind Rose Chart 好吧,不知道怎么翻译,直接用原名。 import plotly....
首先介绍下bokeh bokeh擅长制作交互式图表，当然在地图展示方面也毫不逊色。Bokeh支持google地图、geojson...
Basic Box Plot import plotly.plotly import plotly.graph_objs as go import numpy as np y0 = np.random.randn(50)-1 y1 = np.random.randn(50)+1 trace0 = go.Box( y=y0 ) trace1 = go.Box( y=y1 ) data = [trace0, trace1]
Basic Box Plot 好吧,不知道怎么翻译,直接用原名。 import plotly.plotly import plotly.graph_objs as go import numpy as np y0 = np.random.randn(50)-1 y1 = np.random.randn(50)+1 trace0 = go.Box( y=y0 ) trace1 = go.Box( y=y1 ...
· 易于开发的绘图工具:matplotlib,matplotlib.pyplot,plotly,plotly.graph_objects 初始化图表 创建新的数据可视化的第一步是让用户为失败做好准备。始终创建一个坐标轴或一个特定的图形对象。这样可以完全控制数据放置的位置和方式。 Plotly已经往前迈出了一步。存在子图时,Plotly图形是用每一行和每一列索引的,不像mat...
Matplotlib for java: A simple graph plot library for java, scala and kotlin with powerful python matplotlib - sh0nk/matplotlib4j
While a scatter plot is an excellent tool for getting a first impression about possible correlation, it certainly isn’t definitive proof of a connection. For an overview of the correlations between different columns, you can use.corr(). If you suspect a correlation between two values, then ...