How to transfer strings into integers with pandas

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I'm trying to transfer strings into integers from the plans_data:

 import pandas as pd
from bs4 import BeautifulSoup
import requests
plans_data = pd.DataFrame(columns = ['Country', 'Currency', 'Mobile', 'Basic', 'Standard', 'Premium'])
for index, row in countries_list.iterrows():
    country = row['ID']  
    url = f'https://help.netflix.com/en/node/24926/{country}'
    page = requests.get(url)
    soup = BeautifulSoup(page.content, "html.parser")
    results = soup.find("table", class_="c-table")
    try:
        plan_country = pd.read_html(results.prettify())[0] #creates a list(!) of dataframe objects
        plan_country = plan_country.rename(columns = {'Unnamed: 0':'Currency'})
        plan_country = pd.DataFrame(plan_country.iloc[0,:]).transpose()
        plans_data = pd.concat([plans_data, plan_country], ignore_index=True)
    except AttributeError:
        country_name = row['Name']
        print(f'No data found for {country_name}.')
    plans_data.loc[index, 'Country'] = row['Name']
plans_data

Firstly, I atempted to transfer using function float:

 # 1. Here we import pandas
 import pandas as pd
 # 2. Here we import numpy
 import numpy as np
 ans_2_1_ = float(plans_data['Basic', 'Standard', 'Premium'])

However, I always get the NameError:

---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
~\AppData\Local\Temp/ipykernel_15368/3072127414.py in <module>
      3 # 2. Here we import numpy
      4 import numpy as np
----> 5 ans_2_1_ = float(plans_data['Basic', 'Standard', 'Premium'])

NameError: name 'plans_data' is not defined

How can I solve this problem?

If my code is not appropriate for my task "transfer strings into integers", can you advise me on how to convert?

pandas nameerror dataframe python-3.x python
1 Answers

The error indicates that the second piece of code does not know what plans_data is, so first make sure they plans_data is defined where you do that, ie in the same file or the same Jupyter notebook

second problem is that plans_data['Basic', 'Standard', 'Premium'] is not valid syntax

Thirdly, and probably is your real question, how to convert the values in those columns to floats.

Elements in columns 'Basic', 'Standard', 'Premium' are strings in currency format eg '£ 5.99'. You can convert them to floats as such (you need to do it for each column):

ans_2_1_ = plans_data['Basic'].str[1:].astype(float)
... # same for Standard and Premium
user_145514260
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