How do I correct the row index-CodePudding

I have extracted the item and price from a receipt in python, creating a database using pandas I get a range index of 1 entry from 0 to 0. have looked on line for quite a while, I have tried it all, nothing seems to change the row index. Here is my code and output.

This is my code

res = re.sub('[^a-zA-z] ', ' ', line) 
r = ' '.join([w for w in res.split() if len(w)>1])
dec = re.findall('\d \.\d ',line)
for item in dec:
    df = pd.DataFrame({'Item': [r], 'Price': [item]})
    df['Price'] = pd.to_numeric(df['Price'], errors='coerce')
    print(df)
print(df.info())

How do I convert this

       Item      Price
 0  BAGGED KALE  2.94 
        Item     Price
 0  ORG PARSLEY  1.98 
       Item       Price
 0  ORG BASIL     1.98
     Item        Price
 0  ORG BASIL    1.98 
       Item       Price
 0  ORG BAY LEAV  1.98
      Item       Price
 0  GV ZUC BLND  1.48

To this

        Item      Price
 0  BAGGED KALE   2.94 
 1  ORG PARSLEY   1.98 
 2  ORG BASIL     1.98
 3  ORG BASIL     1.98 
 4  ORG BAY LEAV  1.98
 5  GV ZUC BLND   1.48

CodePudding user response：

Doesn't simply passing the list to the dataframe help you solve the issue? That is:

df = pd.DataFrame({'Item':r, 'Price':dec})

CodePudding user response：

res = re.sub('[^a-zA-z] ', ' ', line) 
r = ' '.join([w for w in res.split() if len(w)>1])
dec = re.findall('\d \.\d ',line)
full_list = []
for i, item in enumerate(dec):
    full_list.append((item, r[i]))
#     df = pd.DataFrame({'Item': [r], 'Price': [item]})
#     df['Price'] = pd.to_numeric(df['Price'], errors='coerce')
#     print(df)
# print(df.info())
df = pd.DataFrame(full_list, columns=['Price', 'Item'])
print(df)