import pandas as pd
df1 = pd.DataFrame({'ISIN': ['', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', ''],
'Name': ['Transcanada Trust 5.875 08/15/76',
'Bp Capital Markets Plc Flt Perp',
'Transcanada Trust Flt 09/15/79',
'Bp Capital Markets Plc Flt Perp',
'Prudential Financial 5.375% 5/15/45',
'Enbridge Inc Flt 07/15/80 Sr:20-A',
'Enbridge Inc. 6.25% 03/01/78',
'Emera 6.75% 6/15/76-26',
'Scentre Group Trust 2 Flt 09/24/80 Sr:144A',
'Credit Suisse Group AG 7.5 Perp',
'Aegon Funding Corp Ii 5.100% 12/15/49',
'Dte Energy Co 5.250% 12/01/77 Sr:E',
'Dai-Ichi Life Insurance 4%',
'Southern Co Flt 09/15/51 Sr:21-A',
'Prudential Financial 5.625% 6/15/43',
'Southern Co 4.950% 01/30/80 Sr:2020',
'Scentre Group Trust 2 Flt 09/24/80 Sr:144A',
'Metlife Inc 9.25% 4/8/2038 144A',
'American Intl Group 8.175% 5/15/58',
'Southern Co Flt 01/15/51 Sr:B',
19.5],
'Weight': [0.0176, 0.0169, 0.0169, 0.0155,0.0150,0.0127,0.0122,0.0113,0.0110,0.0106,0.0101,0.0100
,0.0099,0.0098,0.0097,0.0093,0.0093,0.0089,0.0086,0.0079,0.0091]})
df2 = pd.DataFrame({'Short Name': ['ABU DHABI COMMER', 'ABU DHABI NATION', 'ABU DHABI NATION',
'ADNOC DRILLING C','TRANSCANADA ALPHA DHABI HOLD','DUBAI ISLAMIC' ,
'EMAAR PROP PJSC','ETISALAT','EMIRATES NBD PJS','INTL HOLDING CO' ,
'FIRST ABU DHABI' ,'SCHLUMBERGER LTD' ,'ERSTE GROUP BANK' ,'OMV AG',
'VERBUND AG', 'ARISTOCRAT LEISU', 'AUST AND NZ BANK', 'AFTERPAY LTD',
'ASX LTD', 'BHP GROUP LTD',19.5],
'ISIN': [ 'AEA000201011','AEA002401015','AEA006101017','AEA007301012','AEA007601015',
'AED000201015','AEE000301011','AEE000401019','AEE000801010','AEI000201014',
'AEN000101016','AN8068571086','AT0000652011','AT0000743059','AT0000746409',
'AU000000ALL7','AU000000ANZ3','AU000000APT1','AU000000ASX7','AU000000BHP4','FLOAT_TEST'] })
def strMergeData(strColumnDf1):
strColumnDf1 = str(strColumnDf1).split()[0]
for strColumnDf2 in df2['Short Name']:
if str(strColumnDf1).upper() in str(strColumnDf2).upper():
return df2[df2['Short Name'] == strColumnDf2]['ISIN'].values[0]
break
else:
pass
df1['ISIN'] = df1.apply(lambda x: strMergeData(x['Name']),axis=1)
print(df1)
Write, Run & Share Python code online using OneCompiler's Python online compiler for free. It's one of the robust, feature-rich online compilers for python language, supporting both the versions which are Python 3 and Python 2.7. Getting started with the OneCompiler's Python editor is easy and fast. The editor shows sample boilerplate code when you choose language as Python or Python2 and start coding.
OneCompiler's python online editor supports stdin and users can give inputs to programs using the STDIN textbox under the I/O tab. Following is a sample python program which takes name as input and print your name with hello.
import sys
name = sys.stdin.readline()
print("Hello "+ name)
Python is a very popular general-purpose programming language which was created by Guido van Rossum, and released in 1991. It is very popular for web development and you can build almost anything like mobile apps, web apps, tools, data analytics, machine learning etc. It is designed to be simple and easy like english language. It's is highly productive and efficient making it a very popular language.
When ever you want to perform a set of operations based on a condition IF-ELSE is used.
if conditional-expression
#code
elif conditional-expression
#code
else:
#code
Indentation is very important in Python, make sure the indentation is followed correctly
For loop is used to iterate over arrays(list, tuple, set, dictionary) or strings.
mylist=("Iphone","Pixel","Samsung")
for i in mylist:
print(i)
While is also used to iterate a set of statements based on a condition. Usually while is preferred when number of iterations are not known in advance.
while condition
#code
There are four types of collections in Python.
List is a collection which is ordered and can be changed. Lists are specified in square brackets.
mylist=["iPhone","Pixel","Samsung"]
print(mylist)
Tuple is a collection which is ordered and can not be changed. Tuples are specified in round brackets.
myTuple=("iPhone","Pixel","Samsung")
print(myTuple)
Below throws an error if you assign another value to tuple again.
myTuple=("iPhone","Pixel","Samsung")
print(myTuple)
myTuple[1]="onePlus"
print(myTuple)
Set is a collection which is unordered and unindexed. Sets are specified in curly brackets.
myset = {"iPhone","Pixel","Samsung"}
print(myset)
Dictionary is a collection of key value pairs which is unordered, can be changed, and indexed. They are written in curly brackets with key - value pairs.
mydict = {
"brand" :"iPhone",
"model": "iPhone 11"
}
print(mydict)
Following are the libraries supported by OneCompiler's Python compiler
| Name | Description |
|---|---|
| NumPy | NumPy python library helps users to work on arrays with ease |
| SciPy | SciPy is a scientific computation library which depends on NumPy for convenient and fast N-dimensional array manipulation |
| SKLearn/Scikit-learn | Scikit-learn or Scikit-learn is the most useful library for machine learning in Python |
| Pandas | Pandas is the most efficient Python library for data manipulation and analysis |
| DOcplex | DOcplex is IBM Decision Optimization CPLEX Modeling for Python, is a library composed of Mathematical Programming Modeling and Constraint Programming Modeling |