Given this list
my_lst = [\'LAC\', \'HOU\', \'03/03 06:11 PM\', \'2.13\', \'1.80\', \'03/03 03:42 PM\']
I want to change its 0th
Reverse the dict, then just apply the lookup to the first 2 elements of your list:
subs = {
"Houston": "HOU",
"L.A. Clippers": "LAC",
}
my_lst = ['LAC', 'HOU', '03/03 06:11 PM', '2.13', '1.80', '03/03 03:42 PM']
my_lst[:2] = map(dict(zip(subs.values(), subs)).get, my_lst[:2])
print my_lst
This is a one-line in pandas ....
df['A'].replace(dict(zip(
['SERVICIOS', 'ECON?MICO', 'ECONOMICO', 'EN ESPECIE'],
['servicios', 'economico', 'economico', 'en especie'])
),regex=True)
If the values are unique, then you can flip the dictionary:
subs = {v:k for k, v in subs.iteritems()}
Then you can use .get()
to get the value from a dictionary, along with a second parameter incase the key is not in the dictionary:
print map(subs.get, my_lst, my_lst)
Prints:
['L.A. Clippers', 'Houston', '03/03 06:11 PM', '2.13', '1.80', '03/03 03:42 PM']
if you want something shorter, you can exploit the series
function in pandas
import pandas as pd
A = ['A','B','A','C','D'] #list we want to replace with a dictionary lookup
B = {'A':1,'B':2,'C':3,'D':4} #dictionary lookup, dict values in B will be mapped to entries in A
C = (pd.Series(A)).map(B) #convert the list to a pandas series temporarily before mapping
D = list(C) # we transform the mapped values (a series object) back to a list
# entries in D = [1,2,1,3,4]
If all values are unique then you should reverse the dict first to get an efficient solution:
>>> subs = {
... "Houston": "HOU",
... "L.A. Clippers": "LAC",
...
... }
>>> rev_subs = { v:k for k,v in subs.iteritems()}
>>> [rev_subs.get(item,item) for item in my_lst]
['L.A. Clippers', 'Houston', '03/03 06:11 PM', '2.13', '1.80', '03/03 03:42 PM']
If you're only trying to updated selected indexes, then try:
indexes = [0, 1]
for ind in indexes:
val = my_lst[ind]
my_lst[ind] = rev_subs.get(val, val)