Changing boolean value in pandas dataframe through function-CodePudding

i'm super new to coding and trying to change a boolean set in a pandas df from True to False. I want to select a certain row, based on a name. My df, df_contacts looks like this:

     name  gender relationship category access          timestamp proof
0    Emma  female         ex-girlfriend   True  1653939064.769388     1 
1   Amber  female         ex-girlfriend   True  1653939064.769388     1 
2    Mark    male              business  False  1653939064.769388     1 
3  Claire  female         ex-girlfriend   True  1653939064.769388     1 
4    Sara  female             co-worker  False  1653939064.769388     1 
5  Marcus    male                friend  False  1653939064.769388     1 
6  George    male          soccer-coach  False  1653939064.769388     1

I want to change the value True, behind Emma's name, into False. How can i write this function based on user_input, and not on index?

I am stuck on this: code

block = str(input('Confirm restricting this contact from seeing your photos? '))
def switch_access (name):
        if block == 'yes':
            df_contacts.loc[df_contacts["access"] == True, False]
        print(df_contacts)

switch_access(name)

CodePudding user response：

This will change it using numpy

import numpy as np
block = str(input('Confirm restricting this contact from seeing your photos? '))
def switch_access (name):
        if block.lower() == 'yes':
            condition_list = [df_contacts['category'] == True, df_contacts['category'] == False]
            choice_list = [False, True]
            df_contacts['category'] = np.where(df_contacts['name'] == name, np.select(condition_list, choice_list, df_contacts['category']), df_contacts['category'])
        return df_contacts

df = switch_access('Emma')
df

I also altered your code a little to make it slightly more fault tolerant

CodePudding user response：

You can use:

block = str(input('Confirm restricting this contact from seeing your photos? '))
def switch_access (name):
        if block == 'yes':
            df_contacts.loc[df_contacts['name'] == name, 'access'] = False
        print(df_contacts)

switch_access('Emma')

Output:

     name  gender relationship category  access     timestamp  proof
0    Emma  female         ex-girlfriend   False  1.653939e 09      1  # True to False
1   Amber  female         ex-girlfriend    True  1.653939e 09      1
2    Mark    male              business   False  1.653939e 09      1
3  Claire  female         ex-girlfriend    True  1.653939e 09      1
4    Sara  female             co-worker   False  1.653939e 09      1
5  Marcus    male                friend   False  1.653939e 09      1
6  George    male          soccer-coach   False  1.653939e 09      1

CodePudding user response：

If you want to read the name along with changing the boolean value, you can use this code...

name = input("Enter name of contact: ")
block = str(input('Confirm restricting this contact from seeing your photos? ')) 
def switch_access(name, block): 
    if block.lower() == 'yes': 
        if df_contacts.loc[df_contacts["name"] == name]['access'][0] == True:
            df_contacts.loc[df_contacts["name"] == name, 'access'] = False
            print(df_contacts.loc[df_contacts["name"] == name])
            
switch_access(name, block)

Output

Enter name of contact: Emma
Confirm restricting this contact from seeing your photos? Yes
   name  gender relationship_category  access     timestamp  proof
0  Emma  female         ex-girlfriend   False  1.653939e 09      1