Plotting a scatter graph from a dataframe

Question

I have a dataframe as follows:

    Metal                   Cost per m^3/$      volume/mm^3
0   Cast Iron               5996.0             20088.253323
1   Medium Carbon Steel     4301.0             12636.050310
2   Alloy Steel             6490.6             9134.975311
3   Stainless Steels        34621.0            29216.210066
8   Titanium Alloys         76500.0            16303.954297

I am wanting to plot the cost vs the volume. How would I plot each point with a different colour and use the metal column as the legend.

And please next time asking, provide some sample dataframe with the code, it took me 5 minutes to reproduce the dataframe and 2 minutes to write the answer. — ImportanceOfBeingErnest
– ImportanceOfBeingErnest, Commented Apr 26, 2017 at 11:38

ImportanceOfBeingErnest · Accepted Answer · 2017-04-26 11:34:18Z

2

You can iterate over the rows of the dataframe and use pyplot.scatter to plot the points.

import pandas as pd
import matplotlib.pyplot as plt

a = ["Cast Iron", "Medium Carbon Steel", "Alloy Steel",
     "Stainless Steels", "Titanium Alloys"]
b = [5996,4301, 6490,34621,76500]
c = [ 20088.253323, 12636.050310, 9134.975311, 29216.210066,16303.954297]

df = pd.DataFrame({"Metal":a, "cost":b, "volume":c})

for row in df.iterrows():
    plt.scatter(row[1]["cost"], row[1]["volume"], 
                c=plt.cm.jet(row[0]/float(len(df))), label=row[1]["Metal"])

plt.legend()
plt.show()

answered Apr 26, 2017 at 11:34

ImportanceOfBeingErnest

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