Hello Everyone, this might be simple and I might just be confused. I hope anyone could please help me out in achieving the following ( Apologies If anything has not been explained properly or is not well structured, this is my first time posting a question, I hope you could please help me out) :

I have few columns in my dataframe.

Note : range is inclusive of the limits. And columns I to K are calculated columns after extracting dataset.

Column A - discrete integer values between [3-20]

Column B - numeric - range [0,10000]

Column C - numeric - range [0,10000]

Column D - numeric - range [0,10000]

Column E - 0 or 1

Column F - 0 or 1

Column G - 0 or 1

Column H - 0 or 1

Column I= column C / column B ( will generate NaN/ inf values so should be careful)

Column J= column D / column C ( will generate NaN/ inf values so should be careful)

Column K= column F / column E ( might contain NaN/ inf values so should be careful)

Column L - Category - a or b

Column M - category - c or d

Column N - category - e or f

I am currently trying to plot Column A vs columns I or J or F or G using seaborn line plot

sns.lineplot(x=‘column A’, y=‘column I/J/F/G’, hue =‘Column H’, data)

Blockquote

- I am able to plot Column A vs Column G/F with hue as Column H. I see the mean of the column H for each discrete value in Column A with a 95% Confidence Interval band. However, I want to understand how does seaborn interpret the y values for the calculated columns I,J. Does it calculate the mean of the column I/J/as :

y value for calculated columns I/J = MEAN (NUMERATOR of the respective column)/ MEAN(DENOMINATOR of respective)

or

Is it just Mean ( column I/J) ?

Further I want to plot column A vs sum(column C)/sum(Column B) , sum(column D)/sum(Column E) with hue as Column H .

Any advice on How I could achieve this using snslineplot? Operations I need to perform on the dataframe, Manipulate the dataframe, reset index, pivot Table etc . Any help/ explanation could be really helpful and will help me learn , please? Thank you.

- Further I am trying to use sns.replot or sns.facetGrid to create multiple plots in the following way without for loops :

```
dfm1 = temp_df1.melt(id_vars=['Column A','Column H','Column L'], value_vars=['Column G', 'Column I','Column J','Column F'])
sns.relplot(data=dfm1, x='Column A'', y='value', col='Column H', hue='Column L',row='variable', kind='line')
```

Although I get the plots, I find the plots for columns I/J incomplete ( suspecting this is due to the NaN or inf values). I receive the following error :

```
invalid value encountered in reduce
invalid value encountered in add
invalid value encountered in reduce
invalid value encountered in multiply
```

Can anyone please help me resolve it. Also would be helpful If you could help me with an effeceint and less code version to plot the following :

x=Column A vs y =For Columns in ( G, I,J,F) for each value ( 0 or 1) in column H with hue = for Columns in (L,M,N) .

So 4x2x3 would give a total of 24 plots.

Any advice, help or references would be extremely helpful. I apologise as I cannot share the data. thanks.