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How to create a list from existing list in python - python

I am having a list in below format. How can i create another list from the existing one with just selected elements.
[{'UserDiscount': 0.0, 'CostTotalInvEOPAmount': 940.0, 'WeekEndingData': u'2016-10-08', 'WeeksOnHand': 0.0, 'UnitTotalInvEOPQuantity': 250.0, 'WeeksOfSales': 0.0, 'UnitCostAmount': 3.76, 'Week': u'2016 Wk 36', 'CostReceiptAmount': 940.0, 'UnitSalesQuantity': 0.0, 'UnitReceiptQuantity': 250.0, 'Demand': 0.0, 'InventoryBOP': 0.0, 'PEMDiscount': 0.0, 'ElasticLift': 0.0, 'StoreCount': 0, 'PriceStatus': 4, 'UnitOnOrderQuantity': None, 'ReceiptSizeContributions': [{u'sizeId': u'e1656ac7-1cc1-40ce-b485-989bba9d758d', u'contribution': 1.0}], 'CostSalesAmount': 0.0, 'LifeCycleProperties': {u'IsAtRegularPrice': False, u'IsAtMarkdown': False, u'IsFinished': False, u'IsPreSeason': True}, 'MardownDiscount': 0.0, 'RecommendedReceipt': 250.0, 'RecommendedReceiptSizeContributions': [{u'sizeId': u'e1656ac7-1cc1-40ce-b485-989bba9d758d', u'contribution': 1.0}], 'UnitTotalInvBOPQuantity': 0.0, 'CostOnOrderAmount': None, 'InventoryEOP': 250.0, 'CostTotalInvBOPAmount': 0.0, 'Receipt': 250.0, 'Sales': 0.0, 'LostSales': 0.0, 'TotalDiscount': 0.0, 'RetailSalesAmount': 0.0},
{'UserDiscount': 0.0, 'CostTotalInvEOPAmount': 940.0, 'WeekEndingData': u'2016-10-15', 'WeeksOnHand': 0.0, 'UnitTotalInvEOPQuantity': 250.0, 'WeeksOfSales': 15.784951285314385, 'UnitCostAmount': 3.76, 'Week': u'2016 Wk 37', 'CostReceiptAmount': 0.0, 'UnitSalesQuantity': 0.0, 'UnitReceiptQuantity': 0.0, 'Demand': 0.0, 'InventoryBOP': 250.0, 'PEMDiscount': 0.0, 'ElasticLift': 0.0, 'StoreCount': 0, 'PriceStatus': 4, 'UnitOnOrderQuantity': None, 'ReceiptSizeContributions': [], 'CostSalesAmount': 0.0, 'LifeCycleProperties': {u'IsAtRegularPrice': False, u'IsAtMarkdown': False, u'IsFinished': False, u'IsPreSeason': True}, 'MardownDiscount': 0.0, 'RecommendedReceipt': 0.0, 'RecommendedReceiptSizeContributions': [], 'UnitTotalInvBOPQuantity': 250.0, 'CostOnOrderAmount': None, 'InventoryEOP': 250.0, 'CostTotalInvBOPAmount': 940.0, 'Receipt': 0.0, 'Sales': 0.0, 'LostSales': 0.0, 'TotalDiscount': 0.0, 'RetailSalesAmount': 0.0}]
My new list will having below elements.
[{'UserDiscount': 0.0, 'CostTotalInvEOPAmount': 940.0, 'WeekEndingData': u'2016-10-08', 'WeeksOnHand': 0.0, 'UnitTotalInvEOPQuantity': 250.0, 'WeeksOfSales': 0.0, 'UnitCostAmount': 3.76, 'Week': u'2016 Wk 36', 'CostReceiptAmount': 940.0, 'UnitSalesQuantity': 0.0, 'UnitReceiptQuantity': 250.0, 'Demand': 0.0, 'InventoryBOP': 0.0, 'PEMDiscount': 0.0, 'ElasticLift': 0.0, 'StoreCount': 0, 'PriceStatus': 4, 'UnitOnOrderQuantity': None, 'CostSalesAmount': 0.0, 'RecommendedReceipt': 250.0, 'RetailSalesAmount': 0.0},
{'UserDiscount': 0.0, 'CostTotalInvEOPAmount': 940.0, 'WeekEndingData': u'2016-10-15', 'WeeksOnHand': 0.0, 'UnitTotalInvEOPQuantity': 250.0, 'WeeksOfSales': 15.784951285314385, 'UnitCostAmount': 3.76, 'Week': u'2016 Wk 37', 'CostReceiptAmount': 0.0, 'UnitSalesQuantity': 0.0, 'UnitReceiptQuantity': 0.0, 'Demand': 0.0, 'InventoryBOP': 250.0, 'PEMDiscount': 0.0, 'ElasticLift': 0.0, 'StoreCount': 0, 'PriceStatus': 4, 'UnitOnOrderQuantity': None, 'CostSalesAmount': 0.0, 'RecommendedReceipt': 0.0, 'RetailSalesAmount': 0.0}]

You have a list with two dictionaries. To filter the dictionaries you can try
keep=[key1,key2] #keys you wanna keep
newList = []
for item in mylist:
d = dict((key,value) for key, value in item.iteritems() if key in keep)
newlist.append(d)
del mylist
Also using funcy you can do a
import funcy
mydict={1:1,2:2,3:3}
keep=[1,2]
funcy.project(mydict,keep)
=> {1: 1, 2: 2}
which is much prettier imho.

You could use the list comprehension https://docs.python.org/3/tutorial/datastructures.html#list-comprehensions
[l for l in your_list if l['UserDiscount'] >= 1 ]
[{'UserDiscount': l['UserDiscount'],'CostTotalInvEOPAmount': l['CostTotalInvEOPAmount']} for l in your_list ]
Using this way you can filter the elements in your list and change the structure of your dicts in the list

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Convert a bytes array into JSON format
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Closed 3 months ago.
I have a variable like this:
result = b'{"Results": {"WebServiceOutput0": [{"Label": 7.0, "f0": 0.0, "f1": 0.0, "f2": 0.0, "f3": 0.0, "f4": 0.0, "f5": 0.0, "f6": 0.0, "f7": 0.0, "f8": 0.0, "f9": 0.0, "f10": 0.0, "f11": 0.0, "f12": 0.0, "f13": 0.0, "f14": 0.0, "f15": 0.0, "f16": 0.0, "f17": 0.0, "f18": 0.0, "f19": 0.0, "f20": 0.0, "f21": 0.0, "f22": 0.0, "f23": 0.0, "f24": 0.0, "f25": 0.0, "f26": 0.0, "f27": 0.0, "f28": 0.0, "f29": 0.0, "f30": 0.0, "f31": 0.0, "f32": 0.0, "f33": 0.0, "f34": 0.0, "f35": 0.0, "f36": 0.0, "f37": 0.0, "f38": 0.0, "f39": 0.0, "f40": 0.0, "f41": 0.0, "f42": 0.0, "f43": 0.0, "f44": 0.0, "f45": 0.0, "f46": 0.0, "f47": 0.0, "f48": 0.0, "f49": 0.0, "f50": 0.0, "f51": 0.0, "f52": 0.0, "f53": 0.0, "f54": 0.0, "f55": 0.0, "f56": 0.0, "f57": 0.0, "f58": 0.0, "f59": 0.0, "f60": 0.0, "f61": 0.0, "f62": 0.0, "f63": 0.0, "f64": 0.0, "f65": 0.0, "f66": 0.0, "f67": 0.0, "f68": 0.0, "f69": 0.0, "f70": 0.0, "f71": 0.0, "f72": 0.0, "f73": 0.0, "f74": 0.0, "f75": 0.0, "f76": 0.0, "f77": 0.0, "f78": 0.0, "f79": 0.0, "f80": 0.0, "f81": 0.0, "f82": 0.0, "f83": 0.0, "f84": 0.0, "f85": 0.0, "f86": 0.0, "f87": 0.0, "f88": 0.0, "f89": 0.0, "f90": 0.0, "f91": 0.0, "f92": 0.0, "f93": 0.0, "f94": 0.0, "f95": 0.0, "f96": 0.0, "f97": 0.0, "f98": 0.0, "f99": 0.0, "f100": 0.0, "f101": 0.0, "f102": 0.0, "f103": 0.0, "f104": 0.0, "f105": 0.0, "f106": 0.0, "f107": 0.0, "f108": 0.0, "f109": 0.0, "f110": 0.0, "f111": 0.0, "f112": 0.0, "f113": 0.0, "f114": 0.0, "f115": 0.0, "f116": 0.0, "f117": 0.0, "f118": 0.0, "f119": 0.0, "f120": 0.0, "f121": 0.0, "f122": 0.0, "f123": 0.0, "f124": 0.0, "f125": 0.0, "f126": 0.0, "f127": 0.0, "f128": 0.0, "f129": 0.0, "f130": 0.0, "f131": 0.0, "f132": 0.0, "f133": 0.0, "f134": 0.0, "f135": 0.0, "f136": 0.0, "f137": 0.0, "f138": 0.0, "f139": 0.0, "f140": 0.0, "f141": 0.0, "f142": 0.0, "f143": 0.0, "f144": 0.0, "f145": 0.0, "f146": 0.0, "f147": 0.0, "f148": 0.0, "f149": 0.0, "f150": 0.0, "f151": 0.0, "f152": 0.0, "f153": 0.0, "f154": 0.0, "f155": 0.0, "f156": 0.0, "f157": 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"f233": 254.0, "f234": 254.0, "f235": 241.0, "f236": 198.0, "f237": 198.0, "f238": 198.0, "f239": 198.0, "f240": 198.0, "f241": 198.0, "f242": 198.0, "f243": 198.0, "f244": 170.0, "f245": 52.0, "f246": 0.0, "f247": 0.0, "f248": 0.0, "f249": 0.0, "f250": 0.0, "f251": 0.0, "f252": 0.0, "f253": 0.0, "f254": 0.0, "f255": 0.0, "f256": 0.0, "f257": 0.0, "f258": 67.0, "f259": 114.0, "f260": 72.0, "f261": 114.0, "f262": 163.0, "f263": 227.0, "f264": 254.0, "f265": 225.0, "f266": 254.0, "f267": 254.0, "f268": 254.0, "f269": 250.0, "f270": 229.0, "f271": 254.0, "f272": 254.0, "f273": 140.0, "f274": 0.0, "f275": 0.0, "f276": 0.0, "f277": 0.0, "f278": 0.0, "f279": 0.0, "f280": 0.0, "f281": 0.0, "f282": 0.0, "f283": 0.0, "f284": 0.0, "f285": 0.0, "f286": 0.0, "f287": 0.0, "f288": 0.0, "f289": 0.0, "f290": 0.0, "f291": 17.0, "f292": 66.0, "f293": 14.0, "f294": 67.0, "f295": 67.0, "f296": 67.0, "f297": 59.0, "f298": 21.0, "f299": 236.0, "f300": 254.0, "f301": 106.0, "f302": 0.0, "f303": 0.0, "f304": 0.0, "f305": 0.0, "f306": 0.0, "f307": 0.0, "f308": 0.0, "f309": 0.0, "f310": 0.0, "f311": 0.0, "f312": 0.0, "f313": 0.0, "f314": 0.0, "f315": 0.0, "f316": 0.0, "f317": 0.0, "f318": 0.0, "f319": 0.0, "f320": 0.0, "f321": 0.0, "f322": 0.0, "f323": 0.0, "f324": 0.0, "f325": 0.0, "f326": 83.0, "f327": 253.0, "f328": 209.0, "f329": 18.0, "f330": 0.0, "f331": 0.0, "f332": 0.0, "f333": 0.0, "f334": 0.0, "f335": 0.0, "f336": 0.0, "f337": 0.0, "f338": 0.0, "f339": 0.0, "f340": 0.0, "f341": 0.0, "f342": 0.0, "f343": 0.0, "f344": 0.0, "f345": 0.0, "f346": 0.0, "f347": 0.0, "f348": 0.0, "f349": 0.0, "f350": 0.0, "f351": 0.0, "f352": 0.0, "f353": 22.0, "f354": 233.0, "f355": 255.0, "f356": 83.0, "f357": 0.0, "f358": 0.0, "f359": 0.0, "f360": 0.0, "f361": 0.0, "f362": 0.0, "f363": 0.0, "f364": 0.0, "f365": 0.0, "f366": 0.0, "f367": 0.0, "f368": 0.0, "f369": 0.0, "f370": 0.0, "f371": 0.0, "f372": 0.0, "f373": 0.0, "f374": 0.0, "f375": 0.0, "f376": 0.0, "f377": 0.0, "f378": 0.0, "f379": 0.0, "f380": 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61.0, "f683": 242.0, "f684": 254.0, "f685": 254.0, "f686": 52.0, "f687": 0.0, "f688": 0.0, "f689": 0.0, "f690": 0.0, "f691": 0.0, "f692": 0.0, "f693": 0.0, "f694": 0.0, "f695": 0.0, "f696": 0.0, "f697": 0.0, "f698": 0.0, "f699": 0.0, "f700": 0.0, "f701": 0.0, "f702": 0.0, "f703": 0.0, "f704": 0.0, "f705": 0.0, "f706": 0.0, "f707": 0.0, "f708": 0.0, "f709": 0.0, "f710": 121.0, "f711": 254.0, "f712": 254.0, "f713": 219.0, "f714": 40.0, "f715": 0.0, "f716": 0.0, "f717": 0.0, "f718": 0.0, "f719": 0.0, "f720": 0.0, "f721": 0.0, "f722": 0.0, "f723": 0.0, "f724": 0.0, "f725": 0.0, "f726": 0.0, "f727": 0.0, "f728": 0.0, "f729": 0.0, "f730": 0.0, "f731": 0.0, "f732": 0.0, "f733": 0.0, "f734": 0.0, "f735": 0.0, "f736": 0.0, "f737": 0.0, "f738": 121.0, "f739": 254.0, "f740": 207.0, "f741": 18.0, "f742": 0.0, "f743": 0.0, "f744": 0.0, "f745": 0.0, "f746": 0.0, "f747": 0.0, "f748": 0.0, "f749": 0.0, "f750": 0.0, "f751": 0.0, "f752": 0.0, "f753": 0.0, "f754": 0.0, "f755": 0.0, "f756": 0.0, "f757": 0.0, "f758": 0.0, "f759": 0.0, "f760": 0.0, "f761": 0.0, "f762": 0.0, "f763": 0.0, "f764": 0.0, "f765": 0.0, "f766": 0.0, "f767": 0.0, "f768": 0.0, "f769": 0.0, "f770": 0.0, "f771": 0.0, "f772": 0.0, "f773": 0.0, "f774": 0.0, "f775": 0.0, "f776": 0.0, "f777": 0.0, "f778": 0.0, "f779": 0.0, "f780": 0.0, "f781": 0.0, "f782": 0.0, "f783": 0.0, "Scored Probabilities_0": 1.7306872933250431e-07, "Scored Probabilities_1": 3.3177526751193424e-09, "Scored Probabilities_2": 6.772526557729492e-07, "Scored Probabilities_3": 5.018638683008445e-05, "Scored Probabilities_4": 3.5781842069911e-11, "Scored Probabilities_5": 4.2981825008019914e-08, "Scored Probabilities_6": 6.350046754243676e-14, "Scored Probabilities_7": 0.9999483485221952, "Scored Probabilities_8": 1.3431149602373933e-07, "Scored Probabilities_9": 4.341226706439234e-07, "Scored Labels": 7.0}]}}'
This is the first time I've seen this type of object. How can I get the value of Scored Probabilities_n (n is from 0 to 9) and the Scored Labels? Furthermore, can I get the maximum value (in this case it should be "Scored Probabilities_7": 0.9999483485221952)?
Even when I tried some ways to get the highest value of the variable but it's somehow difficult:
print(max(result))
125
As I can see, there's no 125 value in the variable. So does it mean the normal calculation can not be done on this too? I expected to see the answer on my question above. Thank you!

You can use:
import json
d = json.loads(result.decode('utf-8'))['Results']['WebServiceOutput0'][0]
d['Scored Labels']
# 1.7306872933250431e-07
max_p = max((k for k in d if k.startswith('Scored Probabilities_')), key=d.get)
# 'Scored Probabilities_7'
d[max_p]
# 0.9999483485221952

I have variables as follows:
J = range (1,16)
T = range (1,9)
x= {} # 0,1 decision variable to be determined
These variables turn into combinations of x[j,t].
I am trying to implement a constraint for unacceptable t types in T for x[j,t] combinations that make the x var = 0.
I have a dictionary 'U' with j's as the key and t types and values stored in a list. Zero value means t is unacceptable, 1 is acceptable. The index is range 1-9, not 0-8. So in the example below, j 2, type 3 (bc its at index 3 on range(1,9)) is the only acceptable value.
{1: [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
2: [0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0],
3: [0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0],
4: [1.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0],
5: [0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0],
6: [1.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0],
7: [0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0],
8: [0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0],
9: [0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0],
10: [0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0],
11: [0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0],
12: [0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0],
13: [0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0],
14: [0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0],
15: [0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0]
}
I am struggling in trying to get the x[j,t] combinations bc of the misaligned index. I set it up like so:
for j,t in x:
if t in U[j]==0:
# do the thing... #addConstr(x[j,t], GRB.EQUAL,0)
So for j 2 the results I need are {(2,1):0, (2,2):0, (2,4):0, (2,5):0, (2,6):0, (2,7):0, (2,8):0} where the index value on range (1,9) becomes the t value in the tupledict.
Any pointers? Thank you!

Assuming your example data is stored in U, what you want to do is:
j_results = []
for j,types in U.items():
results = {}
for t in types:
if t == 0.0:
result[(j,int(t))] = 0
j_results.append(result)
j_results list will contain all results like you described:
for j 2 the results I need are {(2,1):0, (2,2):0, (2,4):0, (2,5):0, (2,6):0, (2,7):0, (2,8):0}
will be in j_result[1] (counter intuitive because your U data start from 1)
Note the int cast, because data you provided has floats, but results you provided are a tuple of ints.

I have a dictionary of dictionary as below how to remove non zero key,values from this
{'abcdef': {'1987': 0.0,
'0544': 0.0,
'0568': 0.0,
'3000': 0.0,
'7095': 0.0,
'75609': 1.0,
'56565': 2.0,
'98656': 3.0,
'756095': 0.0,
'23432': 0.0},
'fgrd': {'1987': 0.0,
'0544': 0.0,
'0568': 0.0,
'3000': 0.0,
'7095': 0.0,
'75609': 1.0,
'56565': 2.0,
'98656': 3.0,
'756095': 0.0,
'23432': 0.0}
}
Tried below,
{key:val for key, val in my_dict.items() if val.values() != 0.0}
and getting AttributeError: 'float' object has no attribute 'values',
Thanks

you have to iterate over the primary dictionary and than look for values in secondary dict
here is an example:
val = {'abcdef': {'1987': 0.0,
'0544': 0.0,
'0568': 0.0,
'3000': 0.0,
'7095': 0.0,
'75609': 1.0,
'56565': 2.0,
'98656': 3.0,
'756095': 0.0,
'23432': 0.0}}
for dict_k in val:
for dicts in val.values():
for k in dicts.copy():
if dicts[k] != 0.0:
dicts.pop(k)
print(val)

I would like to create a json file viewer in order to iterate through the key/values of the file. For that I decided to go with a qtreewidgetitem where in the first column I would have the key, in the second column the value and in a third column I would like actually to display the values of an numpy array as an image.
For the moment I have written the following script:
# Std
import argparse
import collections
import json
import sys
import numpy as np
# External
from PyQt5 import QtCore
from PyQt5 import QtGui
from PyQt5 import QtWidgets
from PyQt5.QtWidgets import QMainWindow, QApplication, QLabel, QFileDialog, QAction
from PyQt5.QtGui import QIcon, QPixmap
class TextToTreeItem:
def __init__(self):
self.text_list = []
self.titem_list = []
def append(self, text_list, titem):
for text in text_list:
self.text_list.append(text)
self.titem_list.append(titem)
# Return model indices that match string
def find(self, find_str):
titem_list = []
for i, s in enumerate(self.text_list):
if find_str in s:
titem_list.append(self.titem_list[i])
return titem_list
class JsonView(QtWidgets.QWidget):
def __init__(self, fpath):
super(JsonView, self).__init__()
self.find_box = None
self.tree_widget = None
self.text_to_titem = TextToTreeItem()
self.find_str = ""
self.found_titem_list = []
self.found_idx = 0
self.box_name = ""
jfile = open(fpath)
jdata = json.load(jfile, object_pairs_hook=collections.OrderedDict)
box_names = [*self.gen_dict_extract("box_name", jdata)]
result = len(set(box_names)) == 1
if result:
self.box_name = box_names[0]
# Find UI
find_layout = self.make_find_ui()
# Tree
self.tree_widget = QtWidgets.QTreeWidget()
self.tree_widget.setHeaderLabels(["Key", "Value", "Image"])
# self.tree_widget.header().setSectionResizeMode(QtWidgets.QHeaderView.Stretch)
# self.tree_widget.header().setSectionResizeMode(QtWidgets.QHeaderView.ResizeToContents)
root_item = QtWidgets.QTreeWidgetItem([self.box_name])
self.recurse_jdata(jdata, root_item)
self.tree_widget.addTopLevelItem(root_item)
self.tree_widget.expandToDepth(0)
# Add table to layout
layout = QtWidgets.QHBoxLayout()
layout.addWidget(self.tree_widget)
# Group box
gbox = QtWidgets.QGroupBox(fpath)
gbox.setLayout(layout)
layout2 = QtWidgets.QVBoxLayout()
layout2.addLayout(find_layout)
layout2.addWidget(gbox)
self.setLayout(layout2)
def gen_dict_extract(self, key, var):
if isinstance(var,dict) and hasattr(var, 'items'):
for k, v in var.items():
if k == key:
yield v
if isinstance(v, dict):
for result in self.gen_dict_extract(key, v):
yield result
elif isinstance(v, list):
for d in v:
for result in self.gen_dict_extract(key, d):
yield result
elif isinstance(var,list):
for v in var:
if isinstance(v, dict):
for result in self.gen_dict_extract(key, v):
yield result
elif isinstance(v, list):
for d in v:
for result in self.gen_dict_extract(key, d):
yield result
def make_find_ui(self):
# Text box
self.find_box = QtWidgets.QLineEdit()
self.find_box.returnPressed.connect(self.find_button_clicked)
# Find Button
find_button = QtWidgets.QPushButton("Find")
find_button.clicked.connect(self.find_button_clicked)
layout = QtWidgets.QHBoxLayout()
layout.addWidget(self.find_box)
layout.addWidget(find_button)
return layout
def find_button_clicked(self):
find_str = self.find_box.text()
# Very common for use to click Find on empty string
if find_str == "":
return
# New search string
if find_str != self.find_str:
self.find_str = find_str
self.found_titem_list = self.text_to_titem.find(self.find_str)
self.found_idx = 0
else:
item_num = len(self.found_titem_list)
self.found_idx = (self.found_idx + 1) % item_num
self.tree_widget.setCurrentItem(self.found_titem_list[self.found_idx])
def recurse_jdata(self, jdata, tree_widget):
if isinstance(jdata, dict):
for key, val in jdata.items():
self.tree_add_row(key, val, tree_widget)
elif isinstance(jdata, list):
for i, val in enumerate(jdata):
key = str(i)
if isinstance(jdata[i],dict) and 'sens_comp' in jdata[i]:
key = jdata[i]['sens_comp']
self.tree_add_row(key, val, tree_widget)
else:
print("This should never be reached!")
def tree_add_row(self, key, val, tree_widget):
text_list = []
if isinstance(val,list) and key=='sensorData':
text_list.append(key)
val = np.array(val, dtype=object)
# if len(val.shape) != 1:
# val = val.reshape(24,32)
if len(val.shape) == 1:
val = val.reshape(-1,8)
text_list.append(str(val))
row_item = QtWidgets.QTreeWidgetItem([key, str(val)])
elif isinstance(val, dict) or isinstance(val, list):
text_list.append(key)
row_item = QtWidgets.QTreeWidgetItem([key])
self.recurse_jdata(val, row_item)
else:
text_list.append(key)
text_list.append(str(val))
row_item = QtWidgets.QTreeWidgetItem([key, str(val)])
tree_widget.addChild(row_item)
self.text_to_titem.append(text_list, row_item)
class JsonViewer(QtWidgets.QMainWindow):
def __init__(self):
super(JsonViewer, self).__init__()
self.menu_bar()
if len(sys.argv) > 1:
fpath = sys.argv[1]
json_view = JsonView(fpath)
self.setCentralWidget(json_view)
self.resize(640, 480)
self.setWindowTitle("JSON Viewer")
self.show()
def menu_bar (self) :
# filling up a menu bar
bar = self.menuBar()
# File menu
file_menu = bar.addMenu('File')
# adding actions to file menu
open_action = QtWidgets.QAction('Open', self)
close_action = QtWidgets.QAction('Close', self)
file_menu.addAction(open_action)
file_menu.addAction(close_action)
open_action.triggered.connect(self.openPath)
# use `connect` method to bind signals to desired behavior
close_action.triggered.connect(self.close)
def openPath(self):
fpath, _ = QFileDialog.getOpenFileName()
# fpath = sys.argv[1]
json_view = JsonView(fpath)
self.setCentralWidget(json_view)
def keyPressEvent(self, e):
if e.key() == QtCore.Qt.Key_Escape:
self.close()
def main():
qt_app = QtWidgets.QApplication(sys.argv)
json_viewer = JsonViewer()
sys.exit(qt_app.exec_())
if "__main__" == __name__:
main()
and I am trying to visualize the following information (actually all the information is provided as a single line):
[{"aquisTime": "11-18-25-723721", "box_version": "001", "sens_board": "54906430-100", "MACaddr_eth0": "xx:xx:xx:xx:xx:xx", "sensorData": [[0.0, 27.247400283813477, 0.0, 28.69390296936035, 0.0, 28.078027725219727, 0.0, 28.03997230529785, 0.0, 24.897180557250977, 0.0, 24.499963760375977, 0.0, 23.3978214263916, 0.0, 23.5650577545166, 0.0, 23.758142471313477, 0.0, 23.5541934967041, 0.0, 23.370447158813477, 0.0, 24.9819278717041, 0.0, 25.295557022094727, 0.0, 24.3200626373291, 0.0, 24.304040908813477, 0.0, 22.6225528717041], [26.393274307250977, 0.0, 28.582483291625977, 0.0, 27.909997940063477, 0.0, 28.392236709594727, 0.0, 28.00481605529785, 0.0, 25.388696670532227, 0.0, 24.007410049438477, 0.0, 23.434412002563477, 0.0, 23.327539443969727, 0.0, 24.347131729125977, 0.0, 24.070825576782227, 0.0, 24.752283096313477, 0.0, 27.674463272094727, 0.0, 26.057825088500977, 0.0, 24.291162490844727, 0.0, 25.0914249420166, 0.0], [0.0, 26.8185977935791, 0.0, 26.6101016998291, 0.0, 27.82305335998535, 0.0, 28.930749893188477, 0.0, 28.6760196685791, 0.0, 27.718469619750977, 0.0, 24.382287979125977, 0.0, 23.519739151000977, 0.0, 23.821985244750977, 0.0, 23.407678604125977, 0.0, 24.223718643188477, 0.0, 24.299219131469727, 0.0, 26.3620548248291, 0.0, 27.2630558013916, 0.0, 25.204309463500977, 0.0, 24.8760929107666], [24.9536075592041, 0.0, 26.29070472717285, 0.0, 27.222864151000977, 0.0, 29.23284339904785, 0.0, 29.2844181060791, 0.0, 28.030908584594727, 0.0, 26.043237686157227, 0.0, 23.98674964904785, 0.0, 23.5355167388916, 0.0, 23.86419105529785, 0.0, 23.602441787719727, 0.0, 25.0830020904541, 0.0, 25.52703285217285, 0.0, 28.371667861938477, 0.0, 24.92656898498535, 0.0, 26.448205947875977, 0.0], [0.0, 24.1496524810791, 0.0, 25.244165420532227, 0.0, 28.82390785217285, 0.0, 29.858118057250977, 0.0, 28.943506240844727, 0.0, 27.1224308013916, 0.0, 24.10454750061035, 0.0, 23.904870986938477, 0.0, 23.963159561157227, 0.0, 24.309412002563477, 0.0, 24.791040420532227, 0.0, 24.958215713500977, 0.0, 24.861841201782227, 0.0, 25.5935001373291, 0.0, 26.398340225219727, 0.0, 26.2838077545166], [24.494470596313477, 0.0, 24.91155433654785, 0.0, 25.95366859436035, 0.0, 29.70025062561035, 0.0, 29.372522354125977, 0.0, 28.098535537719727, 0.0, 23.87615394592285, 0.0, 23.5194034576416, 0.0, 23.702905654907227, 0.0, 24.23784828186035, 0.0, 24.3256778717041, 0.0, 25.501184463500977, 0.0, 23.957300186157227, 0.0, 25.55767250061035, 0.0, 26.024988174438477, 0.0, 27.061059951782227, 0.0], [0.0, 24.3924503326416, 0.0, 24.31902503967285, 0.0, 23.994043350219727, 0.0, 25.83245277404785, 0.0, 27.86760902404785, 0.0, 25.213464736938477, 0.0, 23.697229385375977, 0.0, 24.060327529907227, 0.0, 23.775232315063477, 0.0, 24.02068519592285, 0.0, 24.35552406311035, 0.0, 24.200159072875977, 0.0, 24.88030433654785, 0.0, 25.765466690063477, 0.0, 28.722192764282227, 0.0, 27.34758949279785], [23.411401748657227, 0.0, 24.815515518188477, 0.0, 23.414087295532227, 0.0, 24.96453285217285, 0.0, 26.157678604125977, 0.0, 26.347681045532227, 0.0, 23.301172256469727, 0.0, 24.099145889282227, 0.0, 23.26299476623535, 0.0, 24.131616592407227, 0.0, 24.30022621154785, 0.0, 24.39019203186035, 0.0, 24.499414443969727, 0.0, 25.25078773498535, 0.0, 26.4195499420166, 0.0, 27.547204971313477, 0.0], [0.0, 24.554773330688477, 0.0, 24.415918350219727, 0.0, 24.222986221313477, 0.0, 24.6810245513916, 0.0, 23.302209854125977, 0.0, 23.7110538482666, 0.0, 23.354944229125977, 0.0, 23.07952308654785, 0.0, 23.18279457092285, 0.0, 23.99627113342285, 0.0, 24.1441593170166, 0.0, 24.74578285217285, 0.0, 24.0407657623291, 0.0, 25.646997451782227, 0.0, 28.602624893188477, 0.0, 28.41668128967285], [24.0495548248291, 0.0, 24.94378089904785, 0.0, 23.739587783813477, 0.0, 24.223840713500977, 0.0, 23.817956924438477, 0.0, 24.2690372467041, 0.0, 23.297449111938477, 0.0, 23.4769229888916, 0.0, 22.755701065063477, 0.0, 23.3546085357666, 0.0, 23.5649356842041, 0.0, 24.7673282623291, 0.0, 24.238183975219727, 0.0, 25.415918350219727, 0.0, 28.852258682250977, 0.0, 31.557764053344727, 0.0], [0.0, 25.1708927154541, 0.0, 25.2442569732666, 0.0, 24.75335121154785, 0.0, 24.432580947875977, 0.0, 24.0013370513916, 0.0, 23.95977210998535, 0.0, 24.051660537719727, 0.0, 23.533716201782227, 0.0, 23.4976749420166, 0.0, 23.9699649810791, 0.0, 23.509180068969727, 0.0, 24.4299259185791, 0.0, 23.87346839904785, 0.0, 26.298608779907227, 0.0, 29.81133460998535, 0.0, 32.801963806152344], [24.9686222076416, 0.0, 25.230737686157227, 0.0, 24.12090492248535, 0.0, 24.8330020904541, 0.0, 24.093530654907227, 0.0, 24.13250160217285, 0.0, 23.650781631469727, 0.0, 23.43535804748535, 0.0, 23.201745986938477, 0.0, 24.51177406311035, 0.0, 24.09893226623535, 0.0, 24.20073890686035, 0.0, 24.4957218170166, 0.0, 25.689172744750977, 0.0, 27.99920082092285, 0.0, 33.069358825683594, 0.0], [0.0, 24.984277725219727, 0.0, 24.74541664123535, 0.0, 24.881860733032227, 0.0, 24.8862247467041, 0.0, 24.106897354125977, 0.0, 23.9283390045166, 0.0, 23.67705726623535, 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0.0, 24.381433486938477, 0.0, 23.906152725219727, 0.0, 23.602441787719727, 0.0, 24.921167373657227, 0.0, 23.53264808654785, 0.0, 24.28179359436035], [23.799768447875977, 0.0, 24.031763076782227, 0.0, 23.9113712310791, 0.0, 24.697778701782227, 0.0, 25.040552139282227, 0.0, 24.9445743560791, 0.0, 24.569421768188477, 0.0, 24.967676162719727, 0.0, 24.808618545532227, 0.0, 24.8918399810791, 0.0, 24.226831436157227, 0.0, 24.83172035217285, 0.0, 24.483728408813477, 0.0, 23.321191787719727, 0.0, 24.1885929107666, 0.0, 24.445276260375977, 0.0]], "box_model": "DCSMmax", "sens_serNo": [22], "headerVersion": "0021", "sens_i2cAddr": "0x4", "sens_comp": "MLX90640", "aquisDate": "2019-06-14", "hostname": "4d4nx6", "sens_manuf": "Lexis", "box_name": "DCSMmaxNo.22"}]
Now I have two difficulties which I am trying to address. The above works fine and correctly loads the keys and values of the different fields. However, for the sensor_data key while it is a numpy matrix 24x32, instead of showing it in that form what I get is an output where my matrix is formed with multiple line breaks (\n):
which I do not really understand why is happening. The other issue that I would like to address is whether it would be possible to visualize these values as a grayscale image on the third column of my treewidget. Something like below:

I managed to solve my problem by using the pyqtgraph external library and creating the following widget structure:
# Tree
self.tree_widget = QtWidgets.QTreeWidget()
self.tree_widget.setHeaderLabels(["Key", "Value", "Image"])
root_item = QtWidgets.QTreeWidgetItem(["Test Item"])
self.tree_widget.addTopLevelItem(root_item)
# Data
val=numpy.random.normal(size=(32, 24, 3))
# Sub-widgets
tableWidget = pyqtgraph.TableWidget(sortable=False)
tableWidget.setData(val)
im1 = pyqtgraph.ImageView()
im1.setImage(val.T)
self.tree_widget.setItemWidget(root_item, 1, tableWidget)
self.tree_widget.setItemWidget(root_item, 2, im1)

So I have a list of lists, where the 7th index of each sublist contains the value I am interested in averaging, however, the numbers must be averaged according to their type. This type to be matched upond can be found at the 11th index of the sublist.
Below is some code I wrote. In this exa
# Open the csv file
opened_file = open('AppleStore.csv')
from csv import reader
read_file = reader(opened_file)
# Store the data as a list or arrays
apps_data = list(read_file)
# idx_num = index number of interest
# list_doc = the list of lists
# row_start = 1
def extract(idx_num,list_doc,row_start=1):
a_list = []
for row in list_doc[row_start:]:
var = row[idx_num]
a_list.append(var)
return a_list
# Use the extract function to get an array
a_list = extract(11, apps_data, 0)
# Find unique elements
a_list_set = set(a_list)
# Create a dictionary with initial values at [0,0]
dic = dict.fromkeys(a_list_set,[0,0])
print(dic)
# Works as intended
#{'Weather': [0, 0], 'Sports': [0, 0], 'Productivity': [0, 0], 'Games': [0, #0], 'News': [0, 0], 'Finance': [0, 0], 'Education': [0, 0], #'Entertainment': [0, 0], 'Health & Fitness': [0, 0], 'Business': [0, 0], #'Social Networking': [0, 0], 'prime_genre': [0, 0], 'Photo & Video': [0, #0], 'Navigation': [0, 0], 'Music': [0, 0], 'Medical': [0, 0], 'Travel': #[0, 0], 'Reference': [0, 0], 'Shopping': [0, 0], 'Utilities': [0, 0], #'Food & Drink': [0, 0], 'Lifestyle': [0, 0], 'Catalogs': [0, 0], 'Book': #[0, 0]}
for row in apps_data[1:]:
price = float(row[4])
genre = row[11]
# Here is the issue:
# I thought that this would allow for the genre instance to be matched to the appropriate key and then I could append my values.
if genre in dic.keys():
dic[genre][0] += 1
dic[genre][1] += (price)
else:
dic[genre][0] = 1
dic[genre][1] = price
print(dic)
## From here I would extract the array contents of the dictionary
for genre in a_list_set:
print(str(genre) + " mean price:" + str(round(dic[genre][1]/dic[genre][0], 2)))
I got this instead.
{'Weather': [7197, 12423.58999999945], 'Sports': [7197, 12423.58999999945], 'Productivity': [7197, 12423.58999999945], 'Games': [7197, 12423.58999999945], 'News': [7197, 12423.58999999945], 'Finance': [7197, 12423.58999999945], 'Education': [7197, 12423.58999999945], 'Entertainment': [7197, 12423.58999999945], 'Health & Fitness': [7197, 12423.58999999945], 'Business': [7197, 12423.58999999945], 'Social Networking': [7197, 12423.58999999945], 'prime_genre': [7197, 12423.58999999945], 'Photo & Video': [7197, 12423.58999999945], 'Navigation': [7197, 12423.58999999945], 'Music': [7197, 12423.58999999945], 'Medical': [7197, 12423.58999999945], 'Travel': [7197, 12423.58999999945], 'Reference': [7197, 12423.58999999945], 'Shopping': [7197, 12423.58999999945], 'Utilities': [7197, 12423.58999999945], 'Food & Drink': [7197, 12423.58999999945], 'Lifestyle': [7197, 12423.58999999945], 'Catalogs': [7197, 12423.58999999945],'Book': [7197, 12423.58999999945]}

We can do this with itertools.groupby; first, we extract the "columns" of concern from our data, constituting the 7th and 11th value of each row, into subset, also sorting by the 11th value.
Then, we use groupby to partition our subset into groups, where each group's members all have the same 2nd element (the original 11th element). We can then use a dict comprehension to get the mean of the 1st element of each group's members.
from itertools import groupby
from operator import itemgetter
from statistics import mean
subset = sorted(((row[6], row[10]) for row in data), key=itemgetter(1))
result = {key: mean(map(itemgetter(0), group)) for key, group in groupby(subset, itemgetter(1))}
print(result)
Some sample data:
[[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -4.926456602181107, 0.0, 0.0, 0.0, 'this'],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -4.261928508086729, 0.0, 0.0, 0.0, 'that'],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 6.582427615396794, 0.0, 0.0, 0.0, 'other'],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.08345371286375847, 0.0, 0.0, 0.0, 'other'],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.6323414510835206, 0.0, 0.0, 0.0, 'this'],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -7.755177634382969, 0.0, 0.0, 0.0, 'this'],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -5.948058847184649, 0.0, 0.0, 0.0, 'that'],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -5.767820549798114, 0.0, 0.0, 0.0, 'other'],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 4.609131600539092, 0.0, 0.0, 0.0, 'this'],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.2106567350536854, 0.0, 0.0, 0.0, 'that'],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -3.1550716372338297, 0.0, 0.0, 0.0, 'other'],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.6037278107842077, 0.0, 0.0, 0.0, 'that'],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -11.819322083983815, 0.0, 0.0, 0.0, 'this'],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 5.441817745217389, 0.0, 0.0, 0.0, 'other'],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.4961079817344718, 0.0, 0.0, 0.0, 'other'],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 8.269603775378254, 0.0, 0.0, 0.0, 'this'],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.42023137240633596, 0.0, 0.0, 0.0, 'this'],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 7.855652365179269, 0.0, 0.0, 0.0, 'this'],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -8.048026683773955, 0.0, 0.0, 0.0, 'that'],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -4.577046681982131, 0.0, 0.0, 0.0, 'this']]
And the result:
{'other': 0.585667907075492,
'that': -3.530217022955171,
'this': -0.9035005758618025}