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Thumbs up! Recommend a Python artifact that can call Matplotlib for drawing without writing a line of code!

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2023-05-12 20:52:041068browse

赞!推荐一款 Python 神器,不写一行代码,就可以调用 Matplotlib 绘图!

Introducing a new drawing artifact: sviewgui.

Introduction to sviewgui

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, histogram Number of bins, color settings for the graph (from cmocean);
  • Ⅲ Save the graph as an editable PDF;
  • Ⅳ The code for drawing the graph is available so that it can Reuse and modify 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 don’t know either!

sviewgui use

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

import sviewgui.sview as sv
sv.buildGUI()

The screenshot is as follows:

赞!推荐一款 Python 神器,不写一行代码,就可以调用 Matplotlib 绘图!

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:

赞!推荐一款 Python 神器,不写一行代码,就可以调用 Matplotlib 绘图!

Click the above select to select the data source:

赞!推荐一款 Python 神器,不写一行代码,就可以调用 Matplotlib 绘图!

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

赞!推荐一款 Python 神器,不写一行代码,就可以调用 Matplotlib 绘图!

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

赞!推荐一款 Python 神器,不写一行代码,就可以调用 Matplotlib 绘图!

#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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