if statement for popping elements in pandas dict-CodePudding

My pandas dict looks like this:

import pandas as pd

data = {'address': ["William J. Clare\\n290 Valley Dr.\\nCasper, WY 82604\\nUSA",
                    "1180 Shelard Tower\\nMinneapolis, MN 55426\\nUSA",
                    "William N. Barnard\\n145 S. Durbin\\nCasper, WY 82601\\nUSA",
                    "215 S 11th ST"]
        }

df = pd.DataFrame(data)
df_dict = df.to_dict('records')

for row in df_dict:
    add = row["address"]
    print(add.split("\\n"), len(add.split("\\n")))

If you see I need to write an if statement to pop the 1st or 1st 2 elements in the dict if len(add.split("\\n")) is equal to 4 then pop the 1st element and if len(add.split("\\n")) is equal to 5 then pop the 1st two elements and save it has a pandas dataframe.

Your help will be greatly appreciated. I am stuck with this because when I give the if statement it says pop operation cannot be applied for str objects.

Thanks

CodePudding user response：

import pandas as pd

data = {'address': ["William J. Clare\\n290 Valley Dr.\\nCasper, WY 82604\\nUSA",
                    "1180 Shelard Tower\\nMinneapolis, MN 55426\\nUSA",
                    "William N. Barnard\\n145 S. Durbin\\nCasper, WY 82601\\nUSA",
                    "215 S 11th ST"]
        }

df = pd.DataFrame(data)
df_dict = df.to_dict('records')

for row in df_dict:
    add = row["address"]
    if len(add.split("\\n"))==4:
       target = add.split("\\n")
       target.pop(0)
       target = '\\n'.join(target)
    if len(add.split("\\n"))==5:
       target = add.split("\\n")
       target.pop(0)
       target.pop(1)
       target = '\\n'.join(target)
    print(target)

CodePudding user response：

The add variable is actually a str.

If you want to remove an element from the splitted list you can do something like that:

import json

import pandas as pd

data = {'address': ["William J. Clare\\n290 Valley Dr.\\nCasper, WY 82604\\nUSA",
                    "1180 Shelard Tower\\nMinneapolis, MN 55426\\nUSA",
                    "William N. Barnard\\n145 S. Durbin\\nCasper, WY 82601\\nUSA",
                    "215 S 11th ST"]
        }

df = pd.DataFrame(data)
df_dict = df.to_dict('records')

for row in df_dict:
    add = row["address"]
    if len(add.split("\\n")) == 5:
        row['address'] = add[2:]
    elif len(add.split("\\n")) == 4:
        row['address'] = add[1:]

print(json.dumps(df_dict, indent=4))

dataframe = pd.DataFrame(df_dict)
print(dataframe)