Faster way to transform full names to surname and initial
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I have a large data frame that I want to merge with another dataset. In order to do so i need to get the names of individuals into a certain format. The function below converts the name in 'column' to the desired format (mostly) and stores it in 'newColumn'.
My question is, is there a better (faster and/or more puthonic) way to do this?
The main aim is to transform full names into surname and initials. ie:
- Novak Djokovic = Djokovic N.
- Jo-Wilfred Tsonga = Tsonga J.W.
- Victor Estrella Burgos = Burgos V.E.
Juan Martin Del Potro = Del Potro J.M.
def convertNames(df,column, newColumn):
df[newColumn] = 'none'
for player in df[column]:
names = player.split(' ')
if len(names) == 2:
if (len(names[0].split('-')) > 1):
newName = names[1]+' '+names[0].split('-')[0][0]+'.'+names[0].split('-')[1][0]+'.'
else:
newName = names[1]+' '+names[0][0]+'.'
elif len(names) == 3:
newName = names[1]+' '+names[2]+' '+names[0][0]+'.'
else:
newName = names[2]+' '+names[3]+' '+names[0][0]+'.'+names[1][0]+'.'
df[newColumn][df[column] == player] = newName
return df
python strings
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up vote
0
down vote
favorite
I have a large data frame that I want to merge with another dataset. In order to do so i need to get the names of individuals into a certain format. The function below converts the name in 'column' to the desired format (mostly) and stores it in 'newColumn'.
My question is, is there a better (faster and/or more puthonic) way to do this?
The main aim is to transform full names into surname and initials. ie:
- Novak Djokovic = Djokovic N.
- Jo-Wilfred Tsonga = Tsonga J.W.
- Victor Estrella Burgos = Burgos V.E.
Juan Martin Del Potro = Del Potro J.M.
def convertNames(df,column, newColumn):
df[newColumn] = 'none'
for player in df[column]:
names = player.split(' ')
if len(names) == 2:
if (len(names[0].split('-')) > 1):
newName = names[1]+' '+names[0].split('-')[0][0]+'.'+names[0].split('-')[1][0]+'.'
else:
newName = names[1]+' '+names[0][0]+'.'
elif len(names) == 3:
newName = names[1]+' '+names[2]+' '+names[0][0]+'.'
else:
newName = names[2]+' '+names[3]+' '+names[0][0]+'.'+names[1][0]+'.'
df[newColumn][df[column] == player] = newName
return df
python strings
add a comment |
up vote
0
down vote
favorite
up vote
0
down vote
favorite
I have a large data frame that I want to merge with another dataset. In order to do so i need to get the names of individuals into a certain format. The function below converts the name in 'column' to the desired format (mostly) and stores it in 'newColumn'.
My question is, is there a better (faster and/or more puthonic) way to do this?
The main aim is to transform full names into surname and initials. ie:
- Novak Djokovic = Djokovic N.
- Jo-Wilfred Tsonga = Tsonga J.W.
- Victor Estrella Burgos = Burgos V.E.
Juan Martin Del Potro = Del Potro J.M.
def convertNames(df,column, newColumn):
df[newColumn] = 'none'
for player in df[column]:
names = player.split(' ')
if len(names) == 2:
if (len(names[0].split('-')) > 1):
newName = names[1]+' '+names[0].split('-')[0][0]+'.'+names[0].split('-')[1][0]+'.'
else:
newName = names[1]+' '+names[0][0]+'.'
elif len(names) == 3:
newName = names[1]+' '+names[2]+' '+names[0][0]+'.'
else:
newName = names[2]+' '+names[3]+' '+names[0][0]+'.'+names[1][0]+'.'
df[newColumn][df[column] == player] = newName
return df
python strings
I have a large data frame that I want to merge with another dataset. In order to do so i need to get the names of individuals into a certain format. The function below converts the name in 'column' to the desired format (mostly) and stores it in 'newColumn'.
My question is, is there a better (faster and/or more puthonic) way to do this?
The main aim is to transform full names into surname and initials. ie:
- Novak Djokovic = Djokovic N.
- Jo-Wilfred Tsonga = Tsonga J.W.
- Victor Estrella Burgos = Burgos V.E.
Juan Martin Del Potro = Del Potro J.M.
def convertNames(df,column, newColumn):
df[newColumn] = 'none'
for player in df[column]:
names = player.split(' ')
if len(names) == 2:
if (len(names[0].split('-')) > 1):
newName = names[1]+' '+names[0].split('-')[0][0]+'.'+names[0].split('-')[1][0]+'.'
else:
newName = names[1]+' '+names[0][0]+'.'
elif len(names) == 3:
newName = names[1]+' '+names[2]+' '+names[0][0]+'.'
else:
newName = names[2]+' '+names[3]+' '+names[0][0]+'.'+names[1][0]+'.'
df[newColumn][df[column] == player] = newName
return df
python strings
python strings
asked 23 mins ago
theotheraussie
634
634
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