Plotting data in Python
↑ UpPlotting with matplotlib
To run this code, you will need to install matplotlib, such as by running mamba install matplotlib. Here is an example script which makes a scatter plot of a data set. The data file is expected to be space-delimited and be organized so that the x-value is the first column, and then all subsequent columns are interpreted as different y-values. You could create such an input text file using awk to parse a more complex file, for example. Here is an example data file:
X1 Y1 Y2 Y3
1 1 1 1
2 2 4 8
3 3 9 27
4 4 16 64
5 5 25 125
#!/usr/bin/env python3
import numpy as np
import matplotlib.pyplot as plt
import sys
# Check command-line arguments
if len(sys.argv) != 2:
print(f"Usage: {sys.argv[0]} datafile.txt")
sys.exit(1)
filename = sys.argv[1]
# Load data, first line is header
header = np.genfromtxt(filename, max_rows=1, dtype=str)
data = np.loadtxt(filename, skiprows=1)
x = data[:, 0]
y_columns = data[:, 1:]
y_labels = header[1:]
# Define a color cycle (Petroff)
colors=["#3f90da","#ffa90e","#bd1f01","#94a4a2","#832db6","#a96b59","#e76300","#b9ac70","#717581","#92dadd"]
n_colors = len(colors)
# Make scatter plot
for i, y in enumerate(y_columns.T):
plt.scatter(x, y, color=colors[i % n_colors], label=y_labels[i])
# Axis labels
plt.xlabel(header[0], fontweight='bold')
plt.ylabel("Y axis label", fontweight='bold')
# Legend
plt.legend()
plt.grid()
plt.tight_layout()
# Show
plt.show()