I get an array form a csv file and I get an list that looks like
my_list = ["Nov '15", '75', '49', '124', '62', '18', '80', '64.5', '', '', '', '', '', '', '', '']
And now I want to fill the spots where there is '' with an array of items that is that length, lets say the array I want to put in there is
new_array = [1,2,3,4,5,6,7,8]
here is what I am trying but it doesn't work.
i = 0
for item in new_array:
index = 8+i
print item
my_list.insert(index, item)
i += 0
It doesn't change anything my_list is just the same?
How can I change this?
Thanks
Try this:
i = 8
for item in new_array:
my_list[i] = item # you want to replace the value
i += 1 # you forgot to increment the variable
You weren't incrementing the variable i, and insert() moves the items to the right, it doesn't substitute them. Of course, a more idiomatic solution would be:
my_list = my_list[:8] + new_array
my_list = ["Nov '15", '75', '49', '124', '62', '18', '80', '64.5', '', '', '', '', '', '', '', '']
new_array = [1,2,3,4,5,6,7,8]
i = 0
for item in new_array:
index = 8+i
print item
my_list.remove('')
my_list.insert(index, item)
i += 1
print my_list
output:
1
2
3
4
5
6
7
8
["Nov '15", '75', '49', '124', '62', '18', '80', '64.5', 1, 2, 3, 4, 5, 6, 7, 8]
Something like this:
new_iter = iter(new_array)
my_list = [i if i != '' else next(new_iter) for i in my_list]
print(my_list)
This code will work with '' (empty strings) starting at any index:
my_list = ["Nov '15", '75', '49', '124', '62', '18', '80', '64.5', '', '', '', '', '', '', '', '']
starts_at = my_list.index('')
amount_of_empty_strings = 0
for i, item in enumerate(my_list):
if item.strip() == "":
my_list[amount_of_empty_strings+starts_at] = amount_of_empty_strings+1
amount_of_empty_strings+=1
print my_list
Output:
["Nov '15", '75', '49', '124', '62', '18', '80', '64.5', 1, 2, 3, 4, 5, 6, 7, 8]
Using list comprehension
>>> new_array = [1,2,3,4,5,6,7,8]
>>> new_array.reverse()
>>> new_array
[8, 7, 6, 5, 4, 3, 2, 1]
>>> [new_array.pop() if item is '' else item for item in my_list]
["Nov '15", '75', '49', '124', '62', '18', '80', '64.5', 1, 2, 3, 4, 5, 6, 7, 8]
OR
>>> from collections import deque
>>> new_array = deque([1,2,3,4,5,6,7,8])
>>> [new_array.popleft() if item is '' else item for item in my_list]
["Nov '15", '75', '49', '124', '62', '18', '80', '64.5', 1, 2, 3, 4, 5, 6, 7, 8]
Related
I have a dictionary like this:
my_dict = {'RuleSet': {'0': {'RuleSetID': '0',
'RuleSetName': 'Allgemein',
'Rules': [{'RulesID': '10',
'RuleName': 'Gemeinde Seiten',
'GroupHits': '2',
'KeyWordGroups': ['100', '101', '102']}]},
'1': {'RuleSetID': '1',
'RuleSetName': 'Portale Berlin',
'Rules': [{'RulesID': '11',
'RuleName': 'Portale Berlin',
'GroupHits': '4',
'KeyWordGroups': ['100', '101', '102', '107']}]},
'6': {'RuleSetID': '6',
'RuleSetName': 'Zwangsvollstr. Berlin',
'Rules': [{'RulesID': '23',
'RuleName': 'Zwangsvollstr. Berlin',
'GroupHits': '1',
'KeyWordGroups': ['100', '101']}]}}}
When using this code snippet it can be transformed into a dataframe:
rules_pd = pd.DataFrame(my_dict['RuleSet'])
rules_pd
The result is:
I would like to make it look like this:
Does anyone know how to tackle this challenge?
Doing from_dict with index
out = pd.DataFrame.from_dict(my_dict['RuleSet'],'index')
Out[692]:
RuleSetID ... Rules
0 0 ... [{'RulesID': '10', 'RuleName': 'Gemeinde Seite...
1 1 ... [{'RulesID': '11', 'RuleName': 'Portale Berlin...
6 6 ... [{'RulesID': '23', 'RuleName': 'Zwangsvollstr....
[3 rows x 3 columns]
#out.columns
#Out[693]: Index(['RuleSetID', 'RuleSetName', 'Rules'], dtype='object')
You could try use Transpose()
rules_pd = pd.DataFrame(my_dict['RuleSet']).transpose()
print(rules_pd)
I have two lists in Python and I'm trying to map the values of one to the other.
List 1 (coordinates):
['7,16', '71,84', '72,48', '36,52', '75,36', '52,28', '76,44', '11,69', '56,35',
'15,21', '32,74', '88,32', '10,74', '61,34', '51,85', '10,75', '55,96',
'94,12', '34,64', '71,59', '76,75', '25,16', '54,100', '62,1', '60,85',
'16,32', '14,77', '40,78', '2,60', '71,4', '78,91', '100,98', '42,32', '37,49',
'49,34', '3,5', '42,77', '39,60', '38,77', '49,40', '40,53', '57,48', '14,99',
'66,67', '10,9', '97,3', '66,76', '86,68', '10,60', '8,87']
List 2 (index):
[3, 2, 3, 3, 3, 3, 3, 1, 3, 3, 2, 3, 1, 3, 2, 1, 2, 3, 2, 3, 2, 3, 2, 3, 2, 3,
1, 2, 1, 3, 2, 2, 3, 3, 3, 3, 2, 2, 2, 3, 3, 3, 1, 2, 3, 3, 2, 2, 1, 1]
For the output, I need to have something like:
cluster_1: [x, y], [a,b]...
cluster_2: [c, d], [e, f]...
cluster_3: [g, h], [o, j]...
I tried doing this in a dictionary, but I can only get it to put in the last coordinate in the for loop for each value. It also always outputs keys starting from 0, and I'm looking to label them starting from 1.
for i in range(len(patients)):
# other stuff
k = 3
for b in range(k):
if cluster == (k - b):
dct['cluster_%s' % b] = patients[i]
which outputs:
{'cluster_0': '97,3', 'cluster_1': '86,68', 'cluster_2': '8,87'}
I've tried using dct['cluster_%s' % b].append(patients[i]) but I get a key error on cluster_0. Any help would be much appreciated!
You can zip your indices and coordinates, then loop over them element-wise and populate a dictionary based on the index.
clusters = {}
for idx, coord in zip(index, coords):
if idx in clusters:
clusters[idx].append(coord.split(','))
else:
clusters[idx] = [coord.split(',')]
result, where clusters[i] refers the the i-th cluster.
>>> clusters
{
3: [['7', '16'], ['72', '48'], ['36', '52'], ['75', '36'], ['52', '28'], ['76', '44'], ['56', '35'], ['15', '21'], ['88', '32'], ['61', '34'], ['94', '12'], ['71', '59'], ['25', '16'], ['62', '1'], ['16', '32'], ['71', '4'], ['42', '32'], ['37', '49'], ['49', '34'], ['3', '5'], ['49', '40'], ['40', '53'], ['57', '48'], ['10', '9'], ['97', '3']],
2: [['71', '84'], ['32', '74'], ['51', '85'], ['55', '96'], ['34', '64'], ['76', '75'], ['54', '100'], ['60', '85'], ['40', '78'], ['78', '91'], ['100', '98'], ['42', '77'], ['39', '60'], ['38', '77'], ['66', '67'], ['66', '76'], ['86', '68']],
1: [['11', '69'], ['10', '74'], ['10', '75'], ['14', '77'], ['2', '60'], ['14', '99'], ['10', '60'], ['8', '87']]
}
You could use defaultdict along with zip:
from collections import defaultdict
clusters = defaultdict(list)
for id, value in zip(cluster_indices, values):
clusters[id].append(value.split(","))
print(dict(clusters)) # {3: [['7', '16'], ['72', '48'], ...
A defaultdict can be converted to a dict with dict(clusters). However, this may not be necessary since defaultdict basically extends dict.
Note: If you need int values, then you may replace value.split(",") with [int(v) for v in value.split(",")] or list(map(int, value.split(","))). Casting them already at this point will save you an iteration later.
from collections import defaultdict
clusters = defaultdict(list)
for id, value in zip(cluster_indices, values):
clusters[id].append([int(v) for v in value.split(",")])
print(dict(clusters)) # {3: [[7, 16], [72, 48], ...
The group-by behaviour extracted to a function groupby (using a lambda function to allow any kind of transformation) so it can be reused:
from collections import defaultdict
def groupby(indices, values, map_fn):
grouped = defaultdict(list)
for id, value in zip(indices, values):
grouped[id].append(map_fn(id, value))
return dict(grouped)
clusters = groupby(cluster_indices, values, lambda _, value: value.split(","))
print(clusters) # {3: [['7', '16'], ['72', '48'], ...
Here just another way by using itertools.groupby:
from itertools import groupby
from operator import itemgetter
data = sorted(zip(cluster_indices, values), key=itemgetter(0))
grouped = groupby(data, key=itemgetter(0))
clusters = {
cluster: [value[1].split(",") for value in list(values)]
for cluster, values in grouped
}
print(clusters) # {3: [['7', '16'], ['72', '48'], ...
However, I would use the defaultdict approach above or Cory Kramer's answer as it is more simple and easier to read (and therefore preferable)!
# File 1
Column = ['1', '2', '3']
# File 2
Column = ['-2', '-6', '-7', '-6', '-7']
# File 3
Column=['0', '3', '4', '6', '5']
# File 4
Column = ['-1', '-2', '-3', '-3', '-3']
# Combined files
Column = ['1', '2', '3', '-2', '-6', '-7', '-6', '-7', '0', '3', '4', '6', '5', '-1', '-2', '-3', '-3', '-3']
Guys, I want to select either max or min value from each file in the combined files.
Expected output:
Column = ['3', '-7', '6', '-3']
Any help will be appreciated!
I think you are asking for the abs maximum value for each column. Try the code below
Column1 = [1, 2, 3]
Column2 = [-2, -6, -7, -6, -7]
Column3 = [0, 3, 4, 6, 5]
Column4 = [-1, -2, -3, -3, -3]
print(max(Column1, key=abs))
print(max(Column2, key=abs))
print(max(Column3, key=abs))
print(max(Column4, key=abs))
Within your lists are strings and not integers so you should first convert them into integers:
--> https://www.geeksforgeeks.org/python-converting-all-strings-in-list-to-integers/
It's the same as asking a person "What's the biggest value of apples, oranges, pears".
After that what you simply do is use the max and min function within python.
Column = [1, 2, 3]
print(max(Column))
--> 3
print(min(Column))
--> 1
I hope I could help a little bit. :)
Use this method
column=[sorted(column1)[random.randint(-1,0)]]
Use one of these.
This method first sort the lists
column=[]
column.append(sorted(column1)[random.randint(-1,0)])
column.append(sorted(column2)[random.randint(-1,0)])
column.append(sorted(column3)[random.randint(-1,0)])
column.appemd(sorted(column4)[random.randint(-1,0)])
column.append(sorted(column5)[random.randint(-1,0)])
Thus use random.choice function
column=[]
column.append(random.choice(max(column1),min(column1)))
column.append(random.choice(max(column2),min(column2)))
column.append(random.choice(max(column3),min(column3)))
column.append(random.choice(max(column4),min(column4)))
column.append(random.choice(max(column5),min(column5)))
I am attempting to create a contract bridge match point scoring system. In the list below the 1st, 3rd, etc. numbers are the pair numbers (players) and the 2nd, 4th etc. numbers are the scores achieved by each pair. So pair 2 scored 430, pair 3 scored 420 and so on.
I want to loop through the list and score as follows:
for each pair score that pair 2 beats they receive 2 points, for each they tie 1 point and where they don't beat they get 0 points. The loop then continues and compares each pair's score in the same way. In the example below, pair 2 gets 7 points (beating 3 other pairs and a tie with 1), pair 7 gets 0 points, pair 6 gets 12 points beating every other pair.
My list (generated from an elasticsearch json object) is:
['2', '430', '3', '420', '4', '460', '5', '400', '7', '0', '1', '430', '6', '480']
The python code I have tried (after multiple variations) is:
nsp_mp = 0
ewp_mp = 0
ns_list = []
for row in arr["hits"]["hits"]:
nsp = row["_source"]["nsp"]
nsscore = row["_source"]["nsscore"]
ns_list.append(nsp)
ns_list.append(nsscore)
print(ns_list)
x = ns_list[1]
for i in range(6): #number of competing pairs
if x > ns_list[1::2][i]:
nsp_mp = nsp_mp + 2
elif x == ns_list[1::2][i]:
nsp_mp = nsp_mp
else:
nsp_mp = nsp_mp + 1
print(nsp_mp)
which produces:
['2', '430', '3', '420', '4', '460', '5', '400', '7', '0', '1', '430', '6', '480']
7
which as per calculation above is correct. But when I try to execute a loop it does not return the correct results.
Maybe the approach is wrong. What is the correct way to do this?
The elasticsearch json object is:
arr = {'took': 0, 'timed_out': False, '_shards': {'total': 5, 'successful': 5, 'skipped': 0, 'failed': 0}, 'hits': {'total': 7, 'max_score': 1.0, 'hits': [{'_index': 'match', '_type': 'score', '_id': 'L_L122cBjpp4O0gQG0qd', '_score': 1.0, '_source': {'tournament_id': 1, 'board_number': '1', 'nsp': '2', 'ewp': '9', 'contract': '3NT', 'by': 'S', 'tricks': '10', 'nsscore': '430', 'ewscore': '0', 'timestamp': '2018-12-23T16:45:32.896151'}}, {'_index': 'match', '_type': 'score', '_id': 'MPL122cBjpp4O0gQHEog', '_score': 1.0, '_source': {'tournament_id': 1, 'board_number': '1', 'nsp': '3', 'ewp': '10', 'contract': '4S', 'by': 'N', 'tricks': '10', 'nsscore': '420', 'ewscore': '0', 'timestamp': '2018-12-23T16:45:33.027631'}}, {'_index': 'match', '_type': 'score', '_id': 'MfL122cBjpp4O0gQHEqk', '_score': 1.0, '_source': {'tournament_id': 1, 'board_number': '1', 'nsp': '4', 'ewp': '11', 'contract': '3NT', 'by': 'N', 'tricks': '11', 'nsscore': '460', 'ewscore': '0', 'timestamp': '2018-12-23T16:45:33.158060'}}, {'_index': 'match', '_type': 'score', '_id': 'MvL122cBjpp4O0gQHUoj', '_score': 1.0, '_source': {'tournament_id': 1, 'board_number': '1', 'nsp': '5', 'ewp': '12', 'contract': '3NT', 'by': 'S', 'tricks': '10', 'nsscore': '400', 'ewscore': '0', 'timestamp': '2018-12-23T16:45:33.285460'}}, {'_index': 'match', '_type': 'score', '_id': 'NPL122cBjpp4O0gQHkof', '_score': 1.0, '_source': {'tournament_id': 1, 'board_number': '1', 'nsp': '7', 'ewp': '14', 'contract': '3NT', 'by': 'S', 'tricks': '8', 'nsscore': '0', 'ewscore': '50', 'timestamp': '2018-12-23T16:45:33.538710'}}, {'_index': 'match', '_type': 'score', '_id': 'LvL122cBjpp4O0gQGkqt', '_score': 1.0, '_source': {'tournament_id': 1, 'board_number': '1', 'nsp': '1', 'ewp': '8', 'contract': '3NT', 'by': 'N', 'tricks': '10', 'nsscore': '430', 'ewscore': '0', 'timestamp': '2018-12-23T16:45:32.405998'}}, {'_index': 'match', '_type': 'score', '_id': 'M_L122cBjpp4O0gQHUqg', '_score': 1.0, '_source': {'tournament_id': 1, 'board_number': '1', 'nsp': '6', 'ewp': '13', 'contract': '4S', 'by': 'S', 'tricks': '11', 'nsscore': '480', 'ewscore': '0', 'timestamp': '2018-12-23T16:45:33.411104'}}]}}
List appears to be a poor data structure for this, I think you are making everything worse by flattening your elasticsearch object.
Note there are a few minor mistakes in listings below - to make sure
I'm not solving someone's homework for free. I also realize this is
not the most efficient way of doing so.
Try with dicts:
1) convert elasticsearch json you have to a dict with a better structure:
scores = {}
for row in arr["hits"]["hits"]:
nsp = row["_source"]["nsp"]
nsscore = row["_source"]["nsscore"]
scores[nsp] = nsscore
This will give you something like this:
{'1': '430',
'2': '430',
'3': '420',
'4': '460',
'5': '400',
'6': '480',
'7': '0'}
2) write a function to calculate pair score:
def calculate_score(pair, scores):
score = 0
for p in scores:
if p == pair:
continue
if scores[p] < scores[pair]:
score += 2 # win
elif scores[p] == scores[pair]:
score += 1
return score
This should give you something like this:
In [13]: calculate_score('1', scores)
Out[13]: 7
In [14]: calculate_score('7', scores)
Out[14]: 0
3) loop over all pairs, calculating scores. I'll leave this as exercise.
The main problem with your code is, that the loop is one short, you have 7 entries. Then you should convert the numbers to int, so that the comparison is correct. In your code, you get for ties 0 points.
Instead of having a list, with flattend pairs, you should use tuple pairs.
ns_list = []
for row in arr["hits"]["hits"]:
nsp = int(row["_source"]["nsp"])
nsscore = int(row["_source"]["nsscore"])
ns_list.append((nsp, nsscore))
print(ns_list)
x = ns_list[0][1]
nsp_mp = 0
for nsp, nsscore in ns_list:
if x > nsscore:
nsp_mp += 2
elif x == nsscore:
nsp_mp += 1
print(nsp_mp)
So we can do it like so:
import itertools
d = [(i['_source']['nsp'], i['_source']['nsscore']) for i in arr['hits']['hits']]
d
[('2', '430'),
('3', '420'),
('4', '460'),
('5', '400'),
('7', '0'),
('1', '430'),
('6', '480')]
c = itertools.combinations(d, 2)
counts = {}
for tup in c:
p1, p2 = tup
if not counts.get(p1[0]):
counts[p1[0]] = 0
if int(p1[1]) > int(p2[1]):
counts[p1[0]] += 1
counts
{'2': 3, '3': 2, '4': 3, '5': 1, '7': 0, '1': 0}
I first convert the list of your score to a dictionary object using itertools, then iterating through each key, and for each key, compare the values available in the list
and add accordingly the score you provided and since in this approach you will always add the value 1 because you will always compare it with itself so at end i decrease 1 from the final score there may be a better approach for this
ls = ['2', '430', '3', '420', '4', '460', '5', '400', '7', '0', '1', '430', '6', '480']
d = dict(itertools.zip_longest(*[iter(ls)] * 2, fillvalue=""))
values= d.values()
for item in d.keys():
score=0
for i in values:
if d[item]>i:
score+=2
elif d[item]==i:
score+=1
else:
pass
print(item,":",score-1)
Output:
2 : 7
3 : 4
4 : 10
5 : 2
7 : 0
1 : 7
6 : 12
I have a lists of lists that I want to convert into a 4 value dictionary where the first value in each list is the key. So for example the list would be:
[['267-10-7633', '66', '85', '74', 0], ['709-40-8165', '71', '96', '34', 0]]
and i want it to be
{"267-10-7633":[66,85,74,0], "709-40-8165", [71,96,34,0] }
You can use a dictionary comprehension:
lst = [['267-10-7633', '66', '85', '74', 0], ['709-40-8165', '71', '96', '34', 0]]
{k: v for k, *v in lst}
# {'267-10-7633': ['66', '85', '74', 0], '709-40-8165': ['71', '96', '34', 0]}
If you are on python2, seems like you can't use *v to unpack multiple elements:
{x[0]: x[1:] for x in lst}
# {'267-10-7633': ['66', '85', '74', 0], '709-40-8165': ['71', '96', '34', 0]}
Didn't take care of the type conversion here. I guess you can refer to other answers as to how to do that.
A dict comprehension to compile the dictionary with a list comprehension to convert the strings to int:
> lst = [['267-10-7633', '66', '85', '74', 0], ['709-40-8165', '71', '96', '34', 0]]
> {l[0]: [int(x) for x in l[1:]] for l in lst}
{'267-10-7633': [66, 85, 74, 0], '709-40-8165': [71, 96, 34, 0]}
A simple and straight forward solution.
lst = [['267-10-7633', '66', '85', '74', 0], ['709-40-8165', '71', '96', '34', 0]]
# create an empty dict
new_dict = {}
# iterate through the list
for item in lst:
# key is first element in the inner list
# value is second element in the inner list
key = item[0]
value = item[1:]
new_dict[key] = value
print new_dict
List comprehensions is suitable in this case
{element[0]: [int(x) for x in element[1:]] for element in\
[['267-10-7633', '66', '85', '74', 0], ['709-40-8165', '71', '96', '34', 0]]}
A simple approach:
your_list = [['267-10-7633', '66', '85', '74', 0], ['709-40-8165', '71', '96', '34', 0]]
dictionary = {}
for item in your_list:
dictionary[item[0]] = [int(i) for i in item[1:]]
print(dictionary)
With list and dict comprehension:
dictionary = {item[0]: [int(i) for i in item[1:]] for item in your_list}
print(dictionary)
In both cases, output:
{'267-10-7633': [66, 85, 74, 0], '709-40-8165': [71, 96, 34, 0]}
ll = [['267-10-7633', '66', '85', '74', 0], ['709-40-8165', '71', '96', '34', 0]]
mydict = {}
for item in ll:
key,*values = item
mydict[key] = values
print(mydict)