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I spent many hours looking for tips how to create categorical plot using Seaborn and Pandas having several Xs to be added on x-axis, but I have not found the solution.

For specified columns from excel (for example: S1_1, S1_2, S1_3) I would like to create one scatterplot with readings - it means for each column header 9 measurements are expected. Please refer to the image to see the data structure in excel. I was unable to find the right function.

I tried with the following code, but this is not what I wanted to achieve.

import pandas as pd import matplotlib.pyplot as plt import seaborn as sns df = pd.read_excel("panda.xlsx") dfx = pd.DataFrame({"CHAR": ["S1_1","S1_2","S1_3"]}) sns.stripplot(x=dfx['CHAR'],y=df['S1_1'],color='black') sns.stripplot(x=dfx['CHAR'],y=df['S1_2'],color='black') sns.stripplot(x=dfx['CHAR'],y=df['S1_3'],color='black') plt.xlabel('X Axis') plt.ylabel('Y Axis') plt.show()

Expected vs obtained plot:

expected vs obtained plot

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  • 1
    1. Including an image of the results of your code would help. 2. What do you want to be different? Commented Dec 29, 2022 at 20:34
  • @The Photon, I have uploaded the outcome and the sketch what is expected under the link: i.sstatic.net/3NEsp.png Commented Dec 29, 2022 at 20:53
  • So you want 9 dots above each x-axis label? Commented Dec 29, 2022 at 20:57
  • Yes, this is exactly what I am looking for. I have been looking for similar example for hours. Commented Dec 29, 2022 at 20:59

1 Answer 1

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You're overthinking things. You don't need to call stripplot separately for each column. I generated new random data since you didn't share yours in a copy-and-pastable form, but stripplot will basically do what I think you want with a very short invocation.

> print(df) S1 S2 S3 S4 0 0.314097 0.678525 0.228356 0.770293 1 0.207790 0.739484 0.965662 0.604426 2 0.975562 0.959384 0.088162 0.265529 3 0.616823 0.902795 0.015561 0.662020 4 0.210507 0.287713 0.660347 0.763312 5 0.763505 0.381314 0.759422 0.257578 6 0.707832 0.912063 0.774681 0.534284 7 0.996891 0.258103 0.313047 0.729142 8 0.121308 0.797310 0.286265 0.757299 > sns.stripplot(data=df[["S1", "S2", "S3"]], color='black') > plt.xlabel("X Axis")

enter image description here

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Right, much simpler than I thought. Powerfull tool. It was my first post on this site I did not expect to get the answer so quickly. Really appreciate your support, thank you!

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