Foreword In data visualization, it is often necessary to partially enlarge the data in a certain interval to obtain a higher contrast visualization effect. The following uses the Matplotlib library of the Python language to implement a simple partial magnification effect. Dependent libraries matplotlib: plotting library numpy: an extended library that supports a large number […]
Tag: matplotlib
Matplotlib_plotting canvas configuration
Canvas Configuration plt.figure() figsize:canvas size, width and height #Import the two libraries numpy and matplotlib.pyplot import numpy as np import matplotlib.pyplot as plt #Created a graphics window with a size of 5×3 inches. plt.figure(figsize=(5, 3)) # Draw sine curve x = np.linspace(0, 2*np.pi) y = np.sin(x) plt.plot(x, y) plt.show() If the canvas size is changed […]
This error originates from a subprocess Termux matplotlib pandas compilation error and jupyter installation issues
Article directory Notice Problem Description ~~Question complaints~~ Solution 3 steps version record 1 Clear pip cache 2 Successful installation of matplotlib matplotlib completes dependent commands 3 Successful installation of pandas Supplementary question 1: `pip install jupyter` error: solution Supplementary question 3: There is a conflict between openblas and libopenblas, causing libopenblas to fail to be […]
matplotlib draws multi-tree dendrogram
Directory code Effect Due to the needs of answering questions, etc., sometimes we need to visualize a tree structure to debug intuitively. Here I use in Python The matplotlib library implements a function for dendrogram visualization plotTree(). This function receives the root node root of the tree and the tuple edges of the edges. It […]
[Teng Xuehui’s second experimental code] Apply Matplotlib to draw icon analysis
import matplotlib.pyplot as plt import numpy as np Pictures displayed inside #Jupter Notebook %matplotlib inline #1.1.1 Line graph np.random.seed(42) #Generate random seeds y = np.random.randn(30) #Generate random numbers plt.plot(y, “r–o”)#Plot: red–dashed line–circle # 1.1.2 Line color, line type, mark shape x = np.random.randn(30) y = np.random.randn(30) plt.title(“Example”) plt.title(“Example”) y1 = np.random.randn(30)#Generate random numbers y2 = […]
Data analysis—-Matplotlib
1. Introduction Matplotlib is a Python 2D plotting library that produces publication-quality graphics in a variety of hardcopy formats and in a cross-platform interactive environment. (Excerpted from Baidu Encyclopedia) 2. Import Need to import before use import matplotlib.pyplot as plt 3. Display charts By default, the image is not displayed directly, and the plt.show() function […]
Pandas+Matplotlib, an in-depth introduction to Python data analysis
Explore charts with visualization 1. Data visualization and exploration diagram Data visualization refers to the presentation of data in the form of graphics or tables. Charts can clearly present the nature of data and the relationships between data or attributes, making it easy for people to interpret the chart. Through the Exploratory Graph, users can […]
The Three Musketeers of Python Data Analysis: Pandas, Matplotlib and Seaborn
Python has powerful data analysis and processing capabilities. To use Python for data analysis, you need to master the three Python packages pandas, matplotlib, and seaborn. Mastering the knowledge of Python data analysis can help us better discover what is behind the data. laws and trends to provide support for business decisions. Reading data using […]
Solve matplotlib\cbook\deprecation.py:107: MatplotlibDeprecationWarning: Passing one of on, true,
Table of Contents Solve matplotlib\cbook\deprecation.py:107: MatplotlibDeprecationWarning: Passing one of ‘on’, ‘true’ as a string is deprecated. Problem Description Solution 1. Use Boolean values instead of strings 2. Remove parameters 3. Update Matplotlib version Summarize 1. Example 1: Draw a chart with a grid 2. Example 2: Adjust the aspect ratio of the chart Introduction to […]
The Three Musketeers of Python Data Analysis: Pandas, Matplotlib and Seaborn
Python has powerful data analysis and processing capabilities. To use Python for data analysis, you need to master the three Python packages: pandas, matplotlib, and seaborn. Mastering the knowledge of Python data analysis can help us better discover data. The laws and trends behind it provide support for business decisions. Reading data using Pandas First, […]