Pandas DataFrame visual

[Truman]

import pandas as pd 
area = pd.Series({'California': 423967, 'Texas': 695662,
                  'New York': 141297, 'Florida': 170312,
                  'Illinois': 149995})
pop = pd.Series({'California': 38332521, 'Texas': 26448193,
                 'New York': 19651127, 'Florida': 19552860,
                 'Illinois': 12882135})
data = pd.DataFrame({'area':area, 'pop':pop})
print(data)

this is how it looks like:

Output:
area       pop
California  423967  38332521
Texas       695662  26448193
New York    141297  19651127
Florida     170312  19552860
Illinois    149995  12882135

instead of

Output:
            area       pop
California  423967  38332521
Texas       695662  26448193
New York    141297  19651127
Florida     170312  19552860
Illinois    149995  12882135

Do you have any suggestion how to move area and pop to the right? It may sound banal but if I was doing this for a client it wouldn't look good.

[snippsat]

this is how it looks like:

No it dos not look like this when i run it.

import pandas as pd

area = pd.Series({'California': 423967, 'Texas': 695662,
                  'New York': 141297, 'Florida': 170312,
                  'Illinois': 149995})
pop = pd.Series({'California': 38332521, 'Texas': 26448193,
                 'New York': 19651127, 'Florida': 19552860,
                 'Illinois': 12882135})
data = pd.DataFrame({'area':area, 'pop':pop})

print(data)

Output:
              area       pop
California  423967  38332521
Texas       695662  26448193
New York    141297  19651127
Florida     170312  19552860
Illinois    149995  12882135

So to make in the way it should possible be reset_index() and rename first column.

>>> data = data.reset_index()
>>> data
        index    area       pop
0  California  423967  38332521
1       Texas  695662  26448193
2    New York  141297  19651127
3     Florida  170312  19552860
4    Illinois  149995  12882135
>>> 
>>> data = data.rename(columns={'index': 'States'})
>>> data
       States    area       pop
0  California  423967  38332521
1       Texas  695662  26448193
2    New York  141297  19651127
3     Florida  170312  19552860
4    Illinois  149995  12882135  

[Truman]

now I get

Output:
index    area       pop
0  California  423967  38332521
1       Texas  695662  26448193
2    New York  141297  19651127
3     Florida  170312  19552860
4    Illinois  149995  12882135

This didn't solve my issue because I don't want to see the ugly 'index' and columns are again not labeled well. On different machines and editors it looks different, I guess.

[snippsat]

This didn't solve my issue because I don't want to see the ugly 'index' and columns are again not labeled well

Because you have not done rename as i did?

On different machines and editors it looks different, I guess.

It should look the same if not using a strange editor
Can do it new online environment like Colab,here a Notebook as see same result as i posted.

[Truman]

After renaming there is again a problem with alignining

Output:
States    area       pop
0  California  423967  38332521
1       Texas  695662  26448193
2    New York  141297  19651127
3     Florida  170312  19552860
4    Illinois  149995  12882135

I use VS Code.

[snippsat]

I use VS Code.

There is no problem in VS Code for me,in output windows or Terminal window the output display is correct.
Only in run as Notebook inside Vs Code using # %%,is not display oaky on first print(),but after fix all is correct.
Here a couple of screenshot.

Running NoteBook # %%
The first show it wrong,but there is not problem in code,see after fix the display is also correct.

I find it also more easy to work with JupyterLab Notebook in Browser where it belong,and not inside Vs Code.

[Truman]

Unfortunately, I don't understand your last comment. Don't see a difference between the two images.
After adding print('-' * 50) columns are aligned. Not sure how this code exactly solved the issue.

[snippsat]

After adding print('-' * 50) columns are aligned. Not sure how this code exactly solved the issue

It's the way you combine Series to a DataFrame.
After States will have no index/column only area and pop.

>>> data.columns
Index(['area', 'pop'], dtype='object')

So to fix this use reset_index() and give a name.

>>> data = data.reset_index()
>>> data.columns
Index(['index', 'area', 'pop'], dtype='object')

# Rename to a useful name
data = data.rename(columns={'index': 'States'})

>>> data.columns
Index(['States', 'area', 'pop'], dtype='object')
>>> 
>>> data
       States    area       pop
0  California  423967  38332521
1       Texas  695662  26448193
2    New York  141297  19651127
3     Florida  170312  19552860
4    Illinois  149995  12882135 

There is no problem in doing this way to fix it.
I don't now how data is collect or that you have to combine two pd.Series like this.
There maybe is a way to make usable DataFrame for raw data,
but using reset_index() is a common way to fix thing to a usable DataFrame.

[hussainmujtaba]

Try using this code

import pandas as pd 
area = pd.Series({'California': 423967, 'Texas': 695662,
                  'New York': 141297, 'Florida': 170312,
                  'Illinois': 149995})
pop = pd.Series({'California': 38332521, 'Texas': 26448193,
                 'New York': 19651127, 'Florida': 19552860,
                 'Illinois': 12882135})
data = pd.DataFrame({'area':area, 'pop':pop},index=area.index)
data.index.name = 'states'

print(data)

Output:
              area       pop
states                      
California  423967  38332521
Texas       695662  26448193
New York    141297  19651127
Florida     170312  19552860
Illinois    149995  12882135

In case you are not familiar with the methods in the above code, go through this article of pandas