[FIXED] Python pandas create a column and add to DataFrame

Issue

I am collecting data from several tables using pandas. I have a list of values from which I would like to add to each row in the table in a loop in the form of a column. And I can't figure out how to do it.

Now the code for combining tables into one looks like this

result_table = []
for url in urls_list:
    
    response = s2.get(url=url, headers=headers)
    soup2 = BS(response.text, 'lxml')

    
    try:
        table = pd.read_html(url) 
    
    except:
        print('table not exist')
        continue
    
    result_table.append(table)


final_table = pd.DataFrame() 

for t in result_table:

    final_table = final_table.append(t)

final_table.to_excel("razmeri.xlsx")

The final_table looks like this:

|  1   | RowTable1   |
|  2   | RowTable1   |
|  3   | RowTable2   |
|  4   | RowTable2   |
|  5   | .........   |

I would like to add list

list = ['259, 178, 305, .....']

and to each row of the table from result_table = value from the list

the final_table should look like this:

| 259   | RowTable1    |
| 259   | RowTable1    |
| 178   | RowTable2    |
| 178   | RowTable2    |
| 305   | RowTable3    |
| 305   | RowTable3    |

I can't figure out how to do it in any way I will be very grateful if someone helps

Version pandas: 1.3.1 python: 3.8.0

Solution

Suppose you have this dataframe:

   Col1       Col2
0     1  RowTable1
1     2  RowTable1
2     3  RowTable2
3     4  RowTable2
4     5  RowTable3

Then you can do:

lst = [259, 178, 305]
it = iter(lst)

df["Col1"] = df.groupby("Col2")["Col1"].transform(lambda x: [next(it, None)] * len(x))
print(df)

Prints:

   Col1       Col2
0   259  RowTable1
1   259  RowTable1
2   178  RowTable2
3   178  RowTable2
4   305  RowTable3

Answered By - Andrej Kesely