Install pip requirements.
pip install matplotlib
pip install pandas
Example of data being used.
Epoch,Connect (NLB),Processing (NLB),Waiting (NLB),Total (NLB),Connect (ALB),Processing (ALB),Waiting (ALB),Total (ALB)
1,57.7,315.7,309.4,321.6,9,104.4,98.3,105.7
2,121.9,114.4,100.3,176.9,5.8,99.1,97.1,101.1
3,5.3,229.4,231.2,231.4,14.2,83,69.4,87.9
4,4.2,134.5,112.2,135.3,5.3,132.4,105.5,134.1
5,5.8,247.4,246.8,248.1,6,74.3,70.2,75.5
6,9.9,122.9,100.6,122.7,7.5,241.1,79.3,242.3
7,6.1,170.2,106.4,170.5,7.2,382.4,375.1,383.8
8,6.6,194.3,201.4,195.5,7.1,130.9,104.8,132.6
9,6.4,146.1,122.3,147.7,9.4,95.6,74,96.4
In the code you can use df as dataframes and use the headers like df["Epoch"].
This is how you get a column data with pandas.
The Python code responsible for generating a chart:
import csv
import sys
import matplotlib.pyplot as plt
import pandas as pd
# Read the data
df = pd.read_csv("data.csv")
# Settings
plt.title("Connect median NLB vs ALB")
plt.tight_layout(pad=2)
fig = plt.gcf()
fig.set_size_inches(10, 4)
# Plotting
plt.plot(df["Epoch"], df["Connect (ALB)"], label = "ALB", color="black", linestyle="-")
plt.plot(df["Epoch"], df["Connect (NLB)"], label = "NLB", color="black", linestyle="--")
# Adding x and y axis labels
plt.xlabel("Epoch", fontstyle="italic")
plt.ylabel("Median value (ms)", fontstyle="italic")
# Legend
legend = plt.legend()
legend.get_frame().set_linewidth(0)
# Export as SVG
plt.savefig("plot.svg", format="svg")
The image above is SVG and you can zoom in and out and check that the image is vector.