How can I change the value of a row with indexing?

Question

I’ve scraped the crypto.com website to get the current prices of crypto coins in DataFrame form, it worked perfectly with pandas, but the ‘Prices’ values are mixed.

here’s the output:

                     Name                           Price 24H CHANGE
0             BBitcoinBTC      16.678,36$16.678,36+0,32%     +0,32%
1            EEthereumETH        $1.230,40$1.230,40+0,52%     +0,52%
2             UTetherUSDT                $1,02$1,02-0,01%     -0,01%
3                 BBNBBNB            $315,46$315,46-0,64%     -0,64%
4           UUSD CoinUSDC                $1,00$1,00+0,00%     +0,00%
5        BBinance USDBUSD                $1,00$1,00+0,00%     +0,00%
6                 XXRPXRP            $0,4067$0,4067-0,13%     -0,13%
7           DDogecoinDOGE           $0,1052$0,1052+13,73%    +13,73%
8             ACardanoADA            $0,3232$0,3232+0,98%     +0,98%
9           MPolygonMATIC            $0,8727$0,8727+1,20%     +1,20%
10           DPolkadotDOT                $5,48$5,48+0,79%     +0,79%

I created a regex to filter the mixed date:

import re

pattern = re.compile(r'($.*)($)')
for value in df['Price']:
    value = pattern.search(value)
    print(value.group(1))

output:

$16.684,53
$1.230,25
$1,02
$315,56
$1,00
$1,00
$0,4078
$0,105
$0,3236
$0,8733

but I couldn’t find a way to change the values. Which is the best way to do it? Thanks.

Asked By: Samuel Martins

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Source

Answer 1

if youre regex expression is good, this would work

df['Price']= df['Price'].apply(lambda x: pattern.search(x).group(1))

Answered By: Andres Ospina

Answer 2

can you try this:

df['price_v2']=df['Price'].apply(lambda x: '$' + x.split('$')[1])

'''
0     $16.678,36+0,32%
1            $1.230,40
2                $1,02
3              $315,46
4                $1,00
5                $1,00
6              $0,4067
7              $0,1052
8              $0,3232
9              $0,8727
10               $5,48
Name: price, dtype: object

Also, BTC looks different from others. Is this a typo you made or is this the response from the api ? If there are parities that look like BTC, we can add an if else block to the code:

df['price']=df['Price'].apply(lambda x: '$' + x.split('$')[1] if x.startswith('$') else '$' + x.split('$')[0])

'''
0     $16.678,36
1      $1.230,40
2          $1,02
3        $315,46
4          $1,00
5          $1,00
6        $0,4067
7        $0,1052
8        $0,3232
9        $0,8727
10         $5,48

'''

Detail:

string = '$1,02$1,02-0,01%'
values = string.split('$') # output -- > ['', '1,02', '1,02-0,01%']
final_value = values[1] # we need only price. Thats why i choose the second element and apply this to all dataframe.

Answered By: Clegane

How can I change the value of a row with indexing?

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