Connected scatterplots are just a mix between scatterplots and linecharts. They are made with the plot function of matplotlib.
If you want to custom them, just check the scatter and line sections!
# libraries import matplotlib.pyplot as plt import numpy as np import pandas as pd import seaborn as sns # data df=pd.DataFrame({'x': range(1,10), 'y': np.random.randn(9)*80+range(1,10) }) # plot plt.plot( 'x', 'y', data=df, linestyle='-', marker='o') plt.show()
How can you smooth this out so that it still goes through the points, but is curved lines rather than lines between each point?
This example doesn’t run with python 3.6. I get errors:
multiple_lines.py:10: RuntimeWarning: Second argument ‘y1’ is ambiguous: could be a color spec but is in data; using as data. Either rename the entry in data or use three arguments to plot.
plt.plot( ‘x’, ‘y1′, data=df, marker=’o’, markerfacecolor=’blue’, markersize=12, color=’skyblue’, linewidth=4)
multiple_lines.py:11: RuntimeWarning: Second argument ‘y2’ is ambiguous: could be a color spec but is in data; using as data. Either rename the entry in data or use three arguments to plot.
plt.plot( ‘x’, ‘y2′, data=df, marker=”, color=’olive’, linewidth=2)
multiple_lines.py:12: RuntimeWarning: Second argument ‘y3’ is ambiguous: could be a color spec but is in data; using as data. Either rename the entry in data or use three arguments to plot.
plt.plot( ‘x’, ‘y3′, data=df, marker=”, color=’olive’, linewidth=2, linestyle=’dashed’, label=”toto”)