TypeError: string indices must be integers with Pandas apply and lambda
Question:
I have below data frame.
dictA = {'Event_ID': {0: 'G-00001', 1: 'G-00002 ', 2: 'G-00003', 3: 'G-00004', 4: 'G-00005', 5: 'G-00006', 6: 'G-00007', 7: 'G-00008', 8: 'G-00009', 9: 'G-00010', 10: 'G-00011', 11: 'G-00012', 12: 'G-00013', 13: 'G-00014', 14: 'G-00015', 15: 'G-00016', 16: 'G-00017'},
'Name': {0: 'ABC', 1: 'CSA', 2: 'CSA', 3: 'VSX', 4: 'ABC', 5: 'ABC', 6: 'CSA', 7: 'ABC', 8: 'VSX', 9: 'CSA', 10: 'VSX', 11: 'ABC', 12: 'VSX', 13: 'VSX', 14: 'ABC', 15: 'ABC', 16: 'CSA'},
'CompanyAd ': {0: '51Job, Inc.Cayman Islands NMS ', 1: "724 Solution's Inc. Canada NMS ", 2: 'A B SKF Sweden OTC+ ', 3: 'A/S Steamship Company Torm Denmark"s NMS OTC+ ', 4: 'ABB Ltd. Switzerland OTC+ ', 5: 'Aber Diamond Ltd. Canada CAP MKT ', 6: 'Abitibi Consolidated Inc. Canada OTC + ', 7: 'ABN Amro Bank N.V. Netherlands AMEX - Preferred OTC+', 8: 'ABN Amro Holding N.V. Netherlands NYSE ', 9: 'Acambis plc United Kingdom OTC + ', 10: "Ace Aviation Holdings'aed Inc. Canada OTC ", 11: 'Acetex Corp. Canada OTC - Debt+ ', 12: 'Acrex Ventures, Ltd. Canada OTC+ ', 13: 'ACS-Tech 80 Ltd. Israel CAP MKT ', 14: 'Actions Semiconductor Co. Ltd. Cayman Islands NMS ', 15: 'Adastra Minerals Inc. Canada OTC* ', 16: 'ADB Systems International Inc. Canada OTC '},
'ticket': {0: 671, 1: 5, 2: 5, 3: 23, 4: 4, 5: 60, 6: 60, 7: 89, 8: 0, 9: 6, 10: 3, 11: 2, 12: 4, 13: 32, 14: 3, 15: 1, 16: 23},
'Revenue': {0: 6720, 1: 56, 2: 78, 3: 34, 4: 89, 5: 73, 6: 345, 7: 890, 8: 0, 9: 45, 10: 39, 11: 34, 12: 89, 13: 127, 14: 84, 15: 100, 16: 525},
'Expences': {0: 150.0, 1: 18.0, 2: 38.0, 3: 23.0, 4: 150.0, 5: 55.0, 6: 110.0, 7: 150.0, 8: 0.0, 9: 16.0, 10: 23.0, 11: 150.0, 12: 48.0, 13: 35.0, 14: 55.0, 15: 150.0, 16: nan},
'expect': {0: 50.0, 1: 100.0, 2: 100.0, 3: nan, 4: 40.0, 5: 60.0, 6: 60.0, 7: nan, 8: 50.0, 9: 60.0, 10: 30.0, 11: 20.0, 12: 40.0, 13: 10.0, 14: 120.0, 15: 140.0, 16: 90.0},
'Signed_Date': {0: Timestamp('2021-06-01 00:00:00'), 1: Timestamp('2021-06-05 00:00:00'), 2: Timestamp('2021-06-03 00:00:00'), 3: Timestamp('2021-06-03 00:00:00'), 4: Timestamp('2021-06-02 00:00:00'), 5: Timestamp('2021-04-15 00:00:00'), 6: Timestamp('2021-06-12 00:00:00'), 7: Timestamp('2021-06-02 00:00:00'), 8: Timestamp('2021-04-30 00:00:00'), 9: Timestamp('2021-06-22 00:00:00'), 10: Timestamp('2021-06-10 00:00:00'), 11: Timestamp('2021-06-03 00:00:00'), 12: Timestamp('2021-06-12 00:00:00'), 13: Timestamp('2021-04-24 00:00:00'), 14: Timestamp('2021-04-21 00:00:00'), 15: Timestamp('2021-06-07 00:00:00'), 16: Timestamp('2021-04-02 00:00:00')}}
df = pd.DataFrame.from_dict(dictA)
Event_ID Name CompanyAd ticket Revenue Expences expect Signed_Date
0 G-00001 ABC 51Job, Inc.Cayman Islands NMS 671 6720 150 50 01 June 2021
1 G-00002 CSA 724 Solution's Inc. Canada NMS 5 56 18 100 05 June 2021
2 G-00003 CSA A B SKF Sweden OTC+ 5 78 38 100 03 June 2021
3 G-00004 VSX A/S Steamship Company Torm Denmark"s NMS OTC+ 23 34 23 NaN 03 June 2021
4 G-00005 ABC ABB Ltd. Switzerland OTC+ 4 89 150 40 02 June 2021
5 G-00006 ABC Aber Diamond Ltd. Canada CAP MKT 60 73 55 60 15 April 2021
6 G-00007 CSA Abitibi Consolidated Inc. Canada OTC + 60 345 110 60 12 June 2021
7 G-00008 ABC ABN Amro Bank N.V. Netherlands AMEX - Preferred OTC+ 89 890 150 NaN 02 June 2021
8 G-00009 VSX ABN Amro Holding N.V. Netherlands NYSE 0 0 0 50 30 April 2021
9 G-00010 CSA Acambis plc United Kingdom OTC + 6 45 16 60 22 June 2021
10 G-00011 VSX Ace Aviation Holdings'aed Inc. Canada OTC 3 39 23 30 10 June 2021
11 G-00012 ABC Acetex Corp. Canada OTC - Debt+ 2 34 150 20 03 June 2021
12 G-00013 VSX Acrex Ventures, Ltd. Canada OTC+ 4 89 48 40 12 June 2021
13 G-00014 VSX ACS-Tech 80 Ltd. Israel CAP MKT 32 127 35 10 24 April 2021
14 G-00015 ABC Actions Semiconductor Co. Ltd. Cayman Islands NMS 3 84 55 120 21 April 2021
15 G-00016 ABC Adastra Minerals Inc. Canada OTC* 1 100 150 140 7 June 2021
16 G-00017 CSA ADB Systems International Inc. Canada OTC 23 525 90 02 April 2021
I want to change the "Name" column value to "ASD" if the "CompanyAd" column contained "OTC+" or "OTC +". I’m using the below code and I’m getting an error, "TypeError: string indices must be integers"
df['account_name_e']=df['CompanyAd '].apply(str).str.replace(" ","")
df['account_name_e'] = df['account_name_e'].apply(str).str.replace("(?i)[^0-9a-z+]",'')
df['NameE'] = df['Name']
df['NameE'] = df['NameE'].apply(lambda row: str('ASD') if 'OTC+' in str(row['account_name_e']) else row)
df
What should I want to do to resolve it?
Thanks in advance!
Answers:
>>> df.loc[df['CompanyAd '].str.contains("OTC+|OTC +"), 'Name'] = "ASD"
>>> df
Event_ID Name CompanyAd ticket Revenue Expences expect Signed_Date
0 G-00001 ABC 51Job, Inc.Cayman Islands NMS 671 6720 150.0 50.0 2021-06-01
1 G-00002 CSA 724 Solution's Inc. Canada NMS 5 56 18.0 100.0 2021-06-05
2 G-00003 ASD A B SKF Sweden OTC+ 5 78 38.0 100.0 2021-06-03
3 G-00004 ASD A/S Steamship Company Torm Denmark"s NMS OTC+ ... 23 34 23.0 NaN 2021-06-03
4 G-00005 ASD ABB Ltd. Switzerland OTC+ 4 89 150.0 40.0 2021-06-02
5 G-00006 ABC Aber Diamond Ltd. Canada CAP MKT ... 60 73 55.0 60.0 2021-04-15
6 G-00007 ASD Abitibi Consolidated Inc. Canada OTC + ... 60 345 110.0 60.0 2021-06-12
7 G-00008 ASD ABN Amro Bank N.V. Netherlands AMEX - Preferre... 89 890 150.0 NaN 2021-06-02
8 G-00009 VSX ABN Amro Holding N.V. Netherlands NYSE ... 0 0 0.0 50.0 2021-04-30
9 G-00010 ASD Acambis plc United Kingdom OTC + 6 45 16.0 60.0 2021-06-22
10 G-00011 ASD Ace Aviation Holdings'aed Inc. Canada OTC ... 3 39 23.0 30.0 2021-06-10
11 G-00012 ASD Acetex Corp. Canada OTC - Debt+ 2 34 150.0 20.0 2021-06-03
12 G-00013 ASD Acrex Ventures, Ltd. Canada OTC+ 4 89 48.0 40.0 2021-06-12
13 G-00014 VSX ACS-Tech 80 Ltd. Israel CAP MKT 32 127 35.0 10.0 2021-04-24
14 G-00015 ABC Actions Semiconductor Co. Ltd. Cayman Islands ... 3 84 55.0 120.0 2021-04-21
15 G-00016 ASD Adastra Minerals Inc. Canada OTC* 1 100 150.0 140.0 2021-06-07
16 G-00017 ASD ADB Systems International Inc. Canada OTC ... 23 525 NaN 90.0 2021-04-02
I have below data frame.
dictA = {'Event_ID': {0: 'G-00001', 1: 'G-00002 ', 2: 'G-00003', 3: 'G-00004', 4: 'G-00005', 5: 'G-00006', 6: 'G-00007', 7: 'G-00008', 8: 'G-00009', 9: 'G-00010', 10: 'G-00011', 11: 'G-00012', 12: 'G-00013', 13: 'G-00014', 14: 'G-00015', 15: 'G-00016', 16: 'G-00017'},
'Name': {0: 'ABC', 1: 'CSA', 2: 'CSA', 3: 'VSX', 4: 'ABC', 5: 'ABC', 6: 'CSA', 7: 'ABC', 8: 'VSX', 9: 'CSA', 10: 'VSX', 11: 'ABC', 12: 'VSX', 13: 'VSX', 14: 'ABC', 15: 'ABC', 16: 'CSA'},
'CompanyAd ': {0: '51Job, Inc.Cayman Islands NMS ', 1: "724 Solution's Inc. Canada NMS ", 2: 'A B SKF Sweden OTC+ ', 3: 'A/S Steamship Company Torm Denmark"s NMS OTC+ ', 4: 'ABB Ltd. Switzerland OTC+ ', 5: 'Aber Diamond Ltd. Canada CAP MKT ', 6: 'Abitibi Consolidated Inc. Canada OTC + ', 7: 'ABN Amro Bank N.V. Netherlands AMEX - Preferred OTC+', 8: 'ABN Amro Holding N.V. Netherlands NYSE ', 9: 'Acambis plc United Kingdom OTC + ', 10: "Ace Aviation Holdings'aed Inc. Canada OTC ", 11: 'Acetex Corp. Canada OTC - Debt+ ', 12: 'Acrex Ventures, Ltd. Canada OTC+ ', 13: 'ACS-Tech 80 Ltd. Israel CAP MKT ', 14: 'Actions Semiconductor Co. Ltd. Cayman Islands NMS ', 15: 'Adastra Minerals Inc. Canada OTC* ', 16: 'ADB Systems International Inc. Canada OTC '},
'ticket': {0: 671, 1: 5, 2: 5, 3: 23, 4: 4, 5: 60, 6: 60, 7: 89, 8: 0, 9: 6, 10: 3, 11: 2, 12: 4, 13: 32, 14: 3, 15: 1, 16: 23},
'Revenue': {0: 6720, 1: 56, 2: 78, 3: 34, 4: 89, 5: 73, 6: 345, 7: 890, 8: 0, 9: 45, 10: 39, 11: 34, 12: 89, 13: 127, 14: 84, 15: 100, 16: 525},
'Expences': {0: 150.0, 1: 18.0, 2: 38.0, 3: 23.0, 4: 150.0, 5: 55.0, 6: 110.0, 7: 150.0, 8: 0.0, 9: 16.0, 10: 23.0, 11: 150.0, 12: 48.0, 13: 35.0, 14: 55.0, 15: 150.0, 16: nan},
'expect': {0: 50.0, 1: 100.0, 2: 100.0, 3: nan, 4: 40.0, 5: 60.0, 6: 60.0, 7: nan, 8: 50.0, 9: 60.0, 10: 30.0, 11: 20.0, 12: 40.0, 13: 10.0, 14: 120.0, 15: 140.0, 16: 90.0},
'Signed_Date': {0: Timestamp('2021-06-01 00:00:00'), 1: Timestamp('2021-06-05 00:00:00'), 2: Timestamp('2021-06-03 00:00:00'), 3: Timestamp('2021-06-03 00:00:00'), 4: Timestamp('2021-06-02 00:00:00'), 5: Timestamp('2021-04-15 00:00:00'), 6: Timestamp('2021-06-12 00:00:00'), 7: Timestamp('2021-06-02 00:00:00'), 8: Timestamp('2021-04-30 00:00:00'), 9: Timestamp('2021-06-22 00:00:00'), 10: Timestamp('2021-06-10 00:00:00'), 11: Timestamp('2021-06-03 00:00:00'), 12: Timestamp('2021-06-12 00:00:00'), 13: Timestamp('2021-04-24 00:00:00'), 14: Timestamp('2021-04-21 00:00:00'), 15: Timestamp('2021-06-07 00:00:00'), 16: Timestamp('2021-04-02 00:00:00')}}
df = pd.DataFrame.from_dict(dictA)
Event_ID Name CompanyAd ticket Revenue Expences expect Signed_Date
0 G-00001 ABC 51Job, Inc.Cayman Islands NMS 671 6720 150 50 01 June 2021
1 G-00002 CSA 724 Solution's Inc. Canada NMS 5 56 18 100 05 June 2021
2 G-00003 CSA A B SKF Sweden OTC+ 5 78 38 100 03 June 2021
3 G-00004 VSX A/S Steamship Company Torm Denmark"s NMS OTC+ 23 34 23 NaN 03 June 2021
4 G-00005 ABC ABB Ltd. Switzerland OTC+ 4 89 150 40 02 June 2021
5 G-00006 ABC Aber Diamond Ltd. Canada CAP MKT 60 73 55 60 15 April 2021
6 G-00007 CSA Abitibi Consolidated Inc. Canada OTC + 60 345 110 60 12 June 2021
7 G-00008 ABC ABN Amro Bank N.V. Netherlands AMEX - Preferred OTC+ 89 890 150 NaN 02 June 2021
8 G-00009 VSX ABN Amro Holding N.V. Netherlands NYSE 0 0 0 50 30 April 2021
9 G-00010 CSA Acambis plc United Kingdom OTC + 6 45 16 60 22 June 2021
10 G-00011 VSX Ace Aviation Holdings'aed Inc. Canada OTC 3 39 23 30 10 June 2021
11 G-00012 ABC Acetex Corp. Canada OTC - Debt+ 2 34 150 20 03 June 2021
12 G-00013 VSX Acrex Ventures, Ltd. Canada OTC+ 4 89 48 40 12 June 2021
13 G-00014 VSX ACS-Tech 80 Ltd. Israel CAP MKT 32 127 35 10 24 April 2021
14 G-00015 ABC Actions Semiconductor Co. Ltd. Cayman Islands NMS 3 84 55 120 21 April 2021
15 G-00016 ABC Adastra Minerals Inc. Canada OTC* 1 100 150 140 7 June 2021
16 G-00017 CSA ADB Systems International Inc. Canada OTC 23 525 90 02 April 2021
I want to change the "Name" column value to "ASD" if the "CompanyAd" column contained "OTC+" or "OTC +". I’m using the below code and I’m getting an error, "TypeError: string indices must be integers"
df['account_name_e']=df['CompanyAd '].apply(str).str.replace(" ","")
df['account_name_e'] = df['account_name_e'].apply(str).str.replace("(?i)[^0-9a-z+]",'')
df['NameE'] = df['Name']
df['NameE'] = df['NameE'].apply(lambda row: str('ASD') if 'OTC+' in str(row['account_name_e']) else row)
df
What should I want to do to resolve it?
Thanks in advance!
>>> df.loc[df['CompanyAd '].str.contains("OTC+|OTC +"), 'Name'] = "ASD"
>>> df
Event_ID Name CompanyAd ticket Revenue Expences expect Signed_Date
0 G-00001 ABC 51Job, Inc.Cayman Islands NMS 671 6720 150.0 50.0 2021-06-01
1 G-00002 CSA 724 Solution's Inc. Canada NMS 5 56 18.0 100.0 2021-06-05
2 G-00003 ASD A B SKF Sweden OTC+ 5 78 38.0 100.0 2021-06-03
3 G-00004 ASD A/S Steamship Company Torm Denmark"s NMS OTC+ ... 23 34 23.0 NaN 2021-06-03
4 G-00005 ASD ABB Ltd. Switzerland OTC+ 4 89 150.0 40.0 2021-06-02
5 G-00006 ABC Aber Diamond Ltd. Canada CAP MKT ... 60 73 55.0 60.0 2021-04-15
6 G-00007 ASD Abitibi Consolidated Inc. Canada OTC + ... 60 345 110.0 60.0 2021-06-12
7 G-00008 ASD ABN Amro Bank N.V. Netherlands AMEX - Preferre... 89 890 150.0 NaN 2021-06-02
8 G-00009 VSX ABN Amro Holding N.V. Netherlands NYSE ... 0 0 0.0 50.0 2021-04-30
9 G-00010 ASD Acambis plc United Kingdom OTC + 6 45 16.0 60.0 2021-06-22
10 G-00011 ASD Ace Aviation Holdings'aed Inc. Canada OTC ... 3 39 23.0 30.0 2021-06-10
11 G-00012 ASD Acetex Corp. Canada OTC - Debt+ 2 34 150.0 20.0 2021-06-03
12 G-00013 ASD Acrex Ventures, Ltd. Canada OTC+ 4 89 48.0 40.0 2021-06-12
13 G-00014 VSX ACS-Tech 80 Ltd. Israel CAP MKT 32 127 35.0 10.0 2021-04-24
14 G-00015 ABC Actions Semiconductor Co. Ltd. Cayman Islands ... 3 84 55.0 120.0 2021-04-21
15 G-00016 ASD Adastra Minerals Inc. Canada OTC* 1 100 150.0 140.0 2021-06-07
16 G-00017 ASD ADB Systems International Inc. Canada OTC ... 23 525 NaN 90.0 2021-04-02