Draw a graph using the data in column 2 of Python's novice Node2 and column 6 of Node4, and then save it in the Figures folder

Asked 1 weeks ago, Updated 1 weeks ago, 1 views

Hello, I have a question because the Python assignment is difficult.

As shown in the screenshot above, each of the four files contains a Pushoverput folder from 00 to 20. Inside this folder are the out files of Node2 and Node4. At this time, the task is to make a code on the Python using the data in column 2 of Node 2 and column 6 of Node 4, draw a graph, and save it in the Figures folder.

In this process, I would like to know a code that can store a total of 22 graphs in the Figures folder, including 00 to 20 graphs using the for statement and a graph with 21 graphs drawn at the same time.

import pandas as pd

import matplotlib.pyplot as plt

csv_test=pd.read_csv(r'C:\Users\Jeong Min\Desktop\Term\0.5H\0.5_00.csv')


I separately extracted data from 00 of 0.5H folders and made a csv file, and I know how to load this file, but I don't know what's next.


2022-09-20 11:41

1 Answers

Hmm. I'll write a very simple example code as an answer.

import pandas as pd
import matplotlib.pyplot as plt

root_dir = "PushoverOutput/"
node2 = pd.read_csv(root_dir + "Node2_Dsp.out", header=None)
node4 = pd.read_csv(root_dir + "Node4_Reaction.out", header=None)

df = pd.DataFrame({"Curvature":node2.iloc[:,1], "Moment":node4.iloc[:,5]})


df.plot.line(x="Curvature", y="Moment", grid=True)
ROOT - PushoverOutput - Node2_Dsp.out

     - - Figures        - result.jpg
     - - script.py

To access a few columns in the Pandas DataFrame, use iloc. Create a data frame by combining two data frames, node2 and node4, into the second (one for index) and sixth (five for index). Then, in a two-column data frame, you draw a graph as a plot function of Pandas.

And then finally, we store that graph as a function of plt.savefig. It might be a little confusing here, but it's plt.savefig because the panda plot function uses matplotlib internally to render.

If you want to adjust the details of the graph, you can study matplotlib a little more.

2022-09-20 11:41

If you have any answers or tips

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