从字典列表中提取键和多个值的 Pythonic 方法

Question

I have some code which works, data is read in from a text file as a list of dicts, the code takes the keys and values from each dict in for loops. While it works I am sure there is a better way to do it than mine below:

Code

data_list = [{'Clk': '190', '50%': '5.3149999999999995', '100%': '4.715'}, 
{'Clk': '195', '50%': '5.295', '100%': '4.765'}, 
{'Clk': '200', '50%': '5.395', '100%': '4.9'}, 
{'Clk': '205', '50%': '5.55', '100%': '4.970000000000001'},
 {'Clk': '210', '50%': '5.68', '100%': '5.005'}, 
 {'Clk': '215', '50%': '5.725', '100%': '5.08'}, 
 {'Clk': '220', '50%': '5.85', '100%': '5.215'}, 
 {'Clk': '225', '50%': '6.03', '100%': '5.35'}, 
 {'Clk': '230', '50%': '6.140000000000001', '100%': '5.395'},
  {'Clk': '235', '50%': '6.074999999999999', '100%': '5.37'}, 
  {'Clk': '240', '50%': '6.02', '100%': '5.345'}, 
  {'Clk': '245', '50%': '6.025', '100%': '5.49'}, 
{'Clk': '290', '50%': '5.67', '100%': '5.37'}]

#print(data_list)
#print('\n'*3)
Clk = []
av_50 = []
av_100 = []
for dicty in data_list:
    for k,v in dicty.items():
        #print("  ", v)
        if k == "Clk":
            Clk.append(dicty["Clk"])
        if k == "50%":
            av_50.append(dicty["50%"])
        if k == "100%":
            av_100.append(dicty["100%"])
print('\n'*3)
print(Clk)
print('\n')
print(av_50)
print('\n')
print(av_100)

Outputs

['190', '195', '200', '205', '210', '215', '220', '225', '230', '235', '240', '245', '290']


['5.3149999999999995', '5.295', '5.395', '5.55', '5.68', '5.725', '5.85', '6.03', '6.140000000000001', '6.074999999999999', '6.02', '6.025', '5.67']


['4.715', '4.765', '4.9', '4.970000000000001', '5.005', '5.08', '5.215', '5.35', '5.395', '5.37', '5.345', '5.49', '5.37']

Answer 1

data_list = [
    {'Clk': '190', '50%': '5.3149999999999995', '100%': '4.715'}, 
    {'Clk': '195', '50%': '5.295', '100%': '4.765'}, 
    {'Clk': '200', '50%': '5.395', '100%': '4.9'}, 
    {'Clk': '205', '50%': '5.55', '100%': '4.970000000000001'},
    {'Clk': '210', '50%': '5.68', '100%': '5.005'}, 
    {'Clk': '215', '50%': '5.725', '100%': '5.08'}, 
    {'Clk': '220', '50%': '5.85', '100%': '5.215'}, 
    {'Clk': '225', '50%': '6.03', '100%': '5.35'}, 
    {'Clk': '230', '50%': '6.140000000000001', '100%': '5.395'},
    {'Clk': '235', '50%': '6.074999999999999', '100%': '5.37'}, 
    {'Clk': '240', '50%': '6.02', '100%': '5.345'}, 
    {'Clk': '245', '50%': '6.025', '100%': '5.49'}, 
    {'Clk': '290', '50%': '5.67', '100%': '5.37'}
]

Clk = [data_point['Clk'] for data_point in data_list] # shortcode for creating list with iterator

av_50 = [data_point['50%'] for data_point in data_list]

av_100 = [data_point['100%'] for data_point in data_list]

Answer 2

You can use zip to go through the dictionaries and map the 3 fields onto individual lists:

data_list = [{'Clk': '190', '50%': '5.3149999999999995', '100%': '4.715'}, 
    {'Clk': '195', '50%': '5.295', '100%': '4.765'}, 
    {'Clk': '200', '50%': '5.395', '100%': '4.9'}, 
    {'Clk': '205', '50%': '5.55', '100%': '4.970000000000001'},
    {'Clk': '210', '50%': '5.68', '100%': '5.005'}, 
    {'Clk': '215', '50%': '5.725', '100%': '5.08'}, 
    {'Clk': '220', '50%': '5.85', '100%': '5.215'}, 
    {'Clk': '225', '50%': '6.03', '100%': '5.35'}, 
    {'Clk': '230', '50%': '6.140000000000001', '100%': '5.395'},
    {'Clk': '235', '50%': '6.074999999999999', '100%': '5.37'}, 
    {'Clk': '240', '50%': '6.02', '100%': '5.345'}, 
    {'Clk': '245', '50%': '6.025', '100%': '5.49'}, 
    {'Clk': '290', '50%': '5.67', '100%': '5.37'}
]

Clk, av_50, av_100 = map(list,zip(*((d["Clk"],d["50%"],d["100%"]) for d in data_list)))

print(Clk)
print(av_50)
print(av_100)

['190', '195', '200', '205', '210', '215', '220', '225', '230', '235', '240', '245', '290']
['5.3149999999999995', '5.295', '5.395', '5.55', '5.68', '5.725', '5.85', '6.03', '6.140000000000001', '6.074999999999999', '6.02', '6.025', '5.67']
['4.715', '4.765', '4.9', '4.970000000000001', '5.005', '5.08', '5.215', '5.35', '5.395', '5.37', '5.345', '5.49', '5.37']

For a more generalized formulation, you can separate the keys from the list comprehension:

keys = ("Clk","50%","100%")
Clk,av_50,av_100 = map(list,zip(*(map(d.get,keys) for d in data_list)))

This would allow creation of a generalized key extraction function:

def listKeys(D,*keys):
    return map(list,zip(*(map(d.get,keys) for d in D)))

Clk,av_50,av_100 = listKeys(data_list,"Clk","50%","100%")

Answer 3

I would recommand using pandas.DataFrame very convenient way to

import pandas as pd

data_list = [{'Clk': '190', '50%': '5.3149999999999995', '100%': '4.715'}, 
{'Clk': '195', '50%': '5.295', '100%': '4.765'}, 
{'Clk': '200', '50%': '5.395', '100%': '4.9'}, 
{'Clk': '205', '50%': '5.55', '100%': '4.970000000000001'},
 {'Clk': '210', '50%': '5.68', '100%': '5.005'}, 
 {'Clk': '215', '50%': '5.725', '100%': '5.08'}, 
 {'Clk': '220', '50%': '5.85', '100%': '5.215'}, 
 {'Clk': '225', '50%': '6.03', '100%': '5.35'}, 
 {'Clk': '230', '50%': '6.140000000000001', '100%': '5.395'},
  {'Clk': '235', '50%': '6.074999999999999', '100%': '5.37'}, 
  {'Clk': '240', '50%': '6.02', '100%': '5.345'}, 
  {'Clk': '245', '50%': '6.025', '100%': '5.49'}, 
{'Clk': '290', '50%': '5.67', '100%': '5.37'}]

my_data=pd.DataFrame(data_list)


clk = my_data['Clk'].tolist()
clk

Regards

Answer 4

Felix's answer works, but if you want to keep the check if the key exists, you could do this:

data_list = [
    {'Clk': '190', '50%': '5.3149999999999995', '100%': '4.715'}, 
    {'Clk': '195', '50%': '5.295', '100%': '4.765'}, 
    {'Clk': '200', '50%': '5.395', '100%': '4.9'}, 
    {'Clk': '205', '50%': '5.55', '100%': '4.970000000000001'},
    {'Clk': '210', '50%': '5.68', '100%': '5.005'}, 
    {'Clk': '215', '50%': '5.725', '100%': '5.08'}, 
    {'Clk': '220', '50%': '5.85', '100%': '5.215'}, 
    {'Clk': '225', '50%': '6.03', '100%': '5.35'}, 
    {'Clk': '230', '50%': '6.140000000000001', '100%': '5.395'},
    {'Clk': '235', '50%': '6.074999999999999', '100%': '5.37'}, 
    {'Clk': '240', '50%': '6.02', '100%': '5.345'}, 
    {'Clk': '245', '50%': '6.025', '100%': '5.49'}, 
    {'Clk': '290', '50%': '5.67', '100%': '5.37'}
]

Clk = [dicty["Clk"] for dicty in data_list if "Clk" in dicty.keys()]
av_50 = [dicty["50%"] for dicty in data_list if "50%" in dicty.keys()]
av_100 = [dicty["100%"] for dicty in data_list if "100%" in dicty.keys()]

Answer 5

Basic (and best) solution without any extra library:

clk = []
av_50 = []
av_100 = []

for item in data_list:
    clk.append(item['Clk'])
    av_50.append(item['50%'])
    av_100.append(item['100%'])

print(clk)
print(av_50)
print(av_100)

More elegant solution with list comprehensions, although less efficient because it requires three iterations over data_list instead of just one required from the previous approach

clk = []
av_50 = []
av_100 = []

clk = [item['Clk'] for item in data_list]
av_50 = [item['50%'] for item in data_list]
av_100 = [item['100%'] for item in data_list]

print(clk)
print(av_50)
print(av_100)

Answer 6

It might convenient to use dynamic collection of data, in case your dict structure might change over time. This will work for your data_list :

def explode(data_list):
    keys = list(data_list[0].keys())
    values = [[d[k] for k in keys] for d in data_list]
    return keys, values

keys, values = explode(data_list)

Then print(keys) outputs

['Clk', '50%', '100%'`]

and print(values) :

[['190', '5.3149999999999995', '4.715'], ['195', '5.295', '4.765'], ['200', '5.395', '4.9'], ['205', '5.55', '4.970000000000001'], ['210', '5.68', '5.005'], ['215', '5.725', '5.08'], ['220', '5.85', '5.215'], ['225', '6.03', '5.35'], ['230', '6.140000000000001', '5.395'], ['235', '6.074999999999999', '5.37'], ['240', '6.02', '5.345'], ['245', '6.025', '5.49'], ['290', '5.67', '5.37']]