How to create a plot of specific row with every column using python and which package to choose matplotlib or seaborn?

Matplotlib vs Seaborn is a question you will probably get mixed opinions on. I personally use matplotlib because I am most familiar and can do more with it. I think - and take this with a grain of salt - that seaborn is a bit easier to use as a beginner but has more limitations than matplotlib.

For your plotting problem, you should first read up on how to access data in a pandas dataframe:
https://pandas.pydata.org/docs/user_guide/indexing.html

When you have gathered your data, you can start plotting it:
https://seaborn.pydata.org/tutorial/introduction.html
https://matplotlib.org/stable/tutorials/introductory/pyplot.html

If you have any specific questions, feel free to ask. But please try to solve your problem yourself first as everything I just posted is readily available through a simple google-search.

Your decimals probably appeared because when you merged the dataframes pandas automatically converted the numerical data from an int type to a float type. If you just want to plot the data, that's not an issue for you. If you still want or need to convert them back to int or similar, you can find help on that here:
https://stackoverflow.com/questions/15891038/change-column-type-in-pandas

Welcome to datascience.stackexchange Saubhik. First, I'd recommend setting your countries column as the index of the dataframe. Say you start with something like this:

`columns = ["Rank2022", "Rank2023", "Countries"]    
    data = [[1.0, 2.0, "Iceland"], [2.0, 3.0, "Norway"], [3.0, 5.0, "Finland"], [4.0, 6.0, "Sweden"], [5.0, 2.0, "Denmark"]]
    df = pd.DataFrame(data, columns=columns)`

you can set the index to the country column:

df = df.set_index("Countries").

Then you can set the type to int:

df = df.astype(int)

And finally you can plot an individual row with something like:

row = df.loc["Norway"]
row.plot()