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----
-title: "Make B/W SVG charts with matplotlib"
-url: make-b-w-svg-charts-with-matplotlib.html
-date: 2023-08-01T17:04:10+02:00
-type: note
-draft: false
----
-
-Install pip requirements.
-
-```sh
-pip install matplotlib
-pip install pandas
-```
-
-Example of data being used.
-
-```text
-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:
-
-```python
-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")
-```
-
-![SVG Chart](/notes/plot.svg)
-
-The image above is SVG and you can zoom in and out and check that the image is vector.