Plotting scatter plot of pandas dataframe with both categorical and numerical data

Question

I am trying to plot a scatter plot of the following type of pandas dataframe:

df = pd.DataFrame([['RH1', 1, 3], ['RH2', 0, 3], ['RH3', 2, 0], ['RH4', 1, 2], columns=['name', 'A', 'B'])

The final plot should have "name" column as Y axis and "A" and "B" as X axis. And the different numerical values with different colours. something like this

I tried to plot it by looping over each row of the dataframe but I got stuck at some place and couldn't do it, the main problem I encounter is the size of both the axis. It would be really great if anyone can help me. Thank you in advance.

Mr. T · Accepted Answer · 2021-01-16T16:40:01.150

You can melt your dataframe and use the values as the column for color:

from matplotlib import pyplot as plt
import pandas as pd

df = pd.DataFrame([['RH1', 1, 3], ['RH2', 0, 3], ['RH3', 2, 0], ['RH4', 1, 2]], columns=['name', 'A', 'B'])

df.melt(["name"]).plot(x="variable", y= "name", kind="scatter", c="value", cmap="plasma")
plt.show()

Sample output:

If you have a limited number of values, you can change the colormap to a discrete colormap and label each color with its value. Alternatively, use seaborn's stripplot:

from matplotlib import pyplot as plt
import pandas as pd
import seaborn as sns

df = pd.DataFrame([['RH1', 1, 3], ['RH2', 0, 3], ['RH3', 2, 0], ['RH4', 1, 2]], columns=['name', 'A', 'B'])

sns.stripplot(data=df.melt(["name"]), x="variable", y= "name", hue="value", jitter=False)
plt.show()

Output:

Thank you so much, it works. I did not know about df.melt() function, it's a great function. Thank you again :) — mohit kushwah, Jan 16 '21 at 16:15

Plotting scatter plot of pandas dataframe with both categorical and numerical data

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