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Another Python artifact, you can call Matplotlib for drawing without writing a line of code!

王林
王林forward
2023-04-13 12:37:021744browse

Another Python artifact, you can call Matplotlib for drawing without writing a line of code!

Introduction to sviewgui

Sviewgui is a PyQt-based GUI for data visualization of csv files or Pandas DataFrames. This GUI is based on matplotlib and you can visualize your csv files in many ways. Main features:

  • Ⅰ Scatter plot, line plot, density plot, histogram and box plot types;
  • Ⅱ Marker size, line width, number of bins for histogram, Settings for the color map (from cmocean);
  • Ⅲ Save the figure as an editable PDF;
  • ⅣThe code for drawing the figure is available so that it can be reused and modified outside of sviewgui;

Project address: https://github.com/SojiroFukuda/sview-gui

This package is super simple to use. It has only one method: buildGUI(). This method can be passed zero or one parameter. You can use the file path of the csv file as an argument, or use a DataFrame object from pandas as an argument. Similar code is written as follows:

# 第一种形式
import sviewgui.sview as sv
sv.buildGUI()
# 第二种形式
import sviewgui.sview as sv
FILE_PATH = "User/Documents/yourdata.csv"
sv.buildGUI(FILE_PATH)
# 第三种形式
import sviewgui.sview as sv
import pandas as pd
FILE_PATH = "User/Documents/yourdata.csv"
df = pd.read_csv(FILE_PATH)
sv.buildGUI(df)

The above code only helps the driver to open this GuI visual interface.

Finally, since this library is based on matplotlib visualization, the seaborn style also applies here, because seaborn is also based on matplotlib visualization.

sviewgui installation

This library has quite a few dependent libraries, so you can directly use the following line of code to install the sviewgui library.

pip install sviewgui -i https://pypi.tuna.tsinghua.edu.cn/simple/ --ignore-installed

I didn’t add the last --ignore-installed at first, but an error was reported. The error is roughly as follows:

ERROR: Cannot uninstall 'certifi'. It is a distutils installed project and thus we cannot
accurately determine which files belong to it which would lead to only a partial uninstall.

Just add this, don’t worry about why, because I also have no idea!

sviewgui use

I introduced 3 codes for opening the GUI graphical interface window above. Here I only introduce the following method:

import sviewgui.sview as sv
sv.buildGUI()

The screenshot is as follows:

Another Python artifact, you can call Matplotlib for drawing without writing a line of code!

When you enter the above code on the command line, it will drive the graphical interface window to open in the background. The initialization state is roughly like this:

Another Python artifact, you can call Matplotlib for drawing without writing a line of code!

Click on the above select to select the data source:

Another Python artifact, you can call Matplotlib for drawing without writing a line of code!

Then we can click on the left menu bar to generate the corresponding graph. But there is one thing, it seems that it does not support Chinese! ! !

Another Python artifact, you can call Matplotlib for drawing without writing a line of code!

#If you feel that this is not enough to perfect the graphics you want, you can copy the Python code corresponding to the graphics and simply modify it.

Another Python artifact, you can call Matplotlib for drawing without writing a line of code!

Then, you can take the following code and simply modify it to generate beautiful Matplotlib graphics.

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import cmocean
#2021/07/13 08:03:18
#- Import CSV as DataFrame ----------
FILE_PATH = 'C:/Users/Administrator/Desktop/plot.csv'
DATA = pd.read_csv(FILE_PATH)
#- Axes Setting ----------
fig, ax = plt.subplots()
ax.set_title( "x-y")
ax.set_xlabel( "x")
ax.set_ylabel( "x" )
ax.set_xlim(min(DATA['x'].replace([np.inf, -np.inf], np.nan ).dropna() ) - abs( min(DATA['x'].replace([np.inf, -np.inf], np.nan ).dropna() )/10), max(DATA['x'].replace([np.inf, -np.inf], np.nan).dropna()) + abs(max(DATA['x'].replace([np.inf, -np.inf], np.nan).dropna())/10))
ax.set_ylim( min(DATA['x'].replace([np.inf, -np.inf], np.nan ).dropna() ) - abs( min(DATA['x'].replace([np.inf, -np.inf], np.nan ).dropna() )/10), max(DATA['x'].replace([np.inf, -np.inf], np.nan).dropna()) + abs(max(DATA['x'].replace([np.inf, -np.inf], np.nan).dropna())/10))
#- PLOT ------------------
ax.plot( DATA["x"].replace([np.inf, -np.inf], np.nan), DATA["x"].replace([np.inf, -np.inf], np.nan), linewidth = 3.0, alpha =1.0, color = "#005AFF" )
plt.show()

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