Scale issues on chart - python

I have a graph below made in plotly(python). I have set graph y-axis in log scale. but I don't know why there are intermediate values between 1000 and 10k like (2,3,4,5,6...). What they are representing? and how they are removed? I must want to remove.
]1
The properties of axis are given below
trace1 = {
"x": [1, 2, 3, 4, 5],
"y": [500, 900, 1100, 10000, 300],
"marker": {
"color": 'rgb(255,140,0)',
},
data = Data([trace1])
layout = {
"autosize": False,
"bargap": 0.0,
"height": 480,
"hovermode": "closest",
"margin": {
"r": 63,
"t": 57,
"b": 52,
"l": 80,
"pad": 0
},
"showlegend": False,
"titlefont": {
"color": "#000000",
"size": 12.0
},
"width": 640,
"xaxis": {
"anchor": "y",
"domain": [0.0, 1.0],
"mirror": "ticks",
"nticks": 9,
"range": [0.5, 10.5],
"showgrid": False,
"showline": True,
"side": "bottom",
"tickfont": {"size": 20.0},
"ticks": "inside",
"title": "x-axes",
"titlefont": {
"color": "black",
"size": 22.0
},
"type": "linear",
"zeroline": False
},
"yaxis": {
"tickmode":'auto',
"ticks":'outside',
"tick0":0,
"dtick":100,
"ticklen":8,
"tickwidth":4,
"anchor": "x",
"mirror": "ticks",
"domain": [0.0, 1.0],
"nticks": 6,
"showgrid": False,
"showline": True,
"side": "left",
"tickfont": {"size": 20.0},
"ticks": "inside",
"title": "y-axis",
"titlefont": {
"color": "black",
"size": 22.0
},
"type": "log",
"zeroline": False,
}
}
fig = dict(data=data, layout=layout)
py.plot(fig, filename='"log-no-log"')


The numbers represent the intermediate multiples until you get to the next order of magnitude. The first 3,4,5 etc. represent multiples of 100 until you reach the tick 1000. Then it will be the markers for multiples of 1000 until you reach 10k. Because of the logarithmic scale, they are not drawn equidistand.
So they might be useful if you want to read from the graph what your value at e.g. x=2 is.

Related

Split Json Data by certain string values (Python)

I want to split incidents by "incidentType" values for python. It always have 5 of these values: period, injuryTime, goal, card and substitution.
Json File
{
"incidents": [
{
"text": "FT",
"homeScore": 2,
"awayScore": 1,
"isLive": false,
"time": 90,
"addedTime": 999,
"incidentType": "period"
},
{
"length": 4,
"time": 90,
"addedTime": 0,
"incidentType": "injuryTime"
},
{
"homeScore": 2,
"awayScore": 1,
"player": {
"name": "Mostafa Mohamed",
"firstName": "",
"lastName": "",
"slug": "mostafa-mohamed",
"shortName": "M. Mohamed",
"position": "F",
"userCount": 3949,
"id": 873551
},
"id": 141786584,
"time": 89,
"isHome": true,
"incidentClass": "penalty",
"incidentType": "goal"
},
{
"player": {
"name": "Duško Tošić",
"slug": "dusko-tosic",
"shortName": "D. Tošić",
"position": "D",
"userCount": 215,
"id": 14557
},
"playerName": "Duško Tošić",
"reason": "Foul",
"id": 119728583,
"time": 85,
"isHome": false,
"incidentClass": "yellow",
"incidentType": "card"
},
{
"playerIn": {
"name": "Younès Belhanda",
"slug": "younes-belhanda",
"shortName": "Y. Belhanda",
"position": "M",
"userCount": 2165,
"id": 72999
},
"playerOut": {
"name": "Martin Linnes",
"slug": "martin-linnes",
"shortName": "M. Linnes",
"position": "D",
"userCount": 339,
"id": 109569
},
"id": 120059400,
"time": 82,
"isHome": true,
"incidentType": "substitution"
},
{
"player": {
"name": "Kevin Varga",
"slug": "kevin-varga",
"shortName": "K. Varga",
"position": "M",
"userCount": 274,
"id": 602730
},
"playerName": "Kevin Varga",
"reason": "Foul",
"id": 119728582,
"time": 82,
"isHome": false,
"incidentClass": "yellow",
"incidentType": "card"
},
{
"playerIn": {
"name": "DeAndre Yedlin",
"slug": "deandre-yedlin",
"shortName": "D. Yedlin",
"position": "D",
"userCount": 702,
"id": 314040
},
"playerOut": {
"name": "Muhammed Kerem Aktürkoğlu",
"firstName": "",
"lastName": "",
"slug": "muhammed-kerem-akturkoglu",
"shortName": "M. K. Aktürkoğlu",
"position": "F",
"userCount": 281,
"id": 903324
},
"id": 120059399,
"time": 77,
"isHome": true,
"incidentType": "substitution"
},
{
"playerIn": {
"name": "Ryan Donk",
"slug": "ryan-donk",
"shortName": "R. Donk",
"position": "D",
"userCount": 489,
"id": 14900
},
"playerOut": {
"name": "Ryan Babel",
"slug": "ryan-babel",
"shortName": "R. Babel",
"position": "F",
"userCount": 1577,
"id": 1876
},
"id": 120059397,
"time": 72,
"isHome": true,
"incidentType": "substitution"
},
{
"playerIn": {
"name": "Emre Akbaba",
"slug": "emre-akbaba",
"shortName": "E. Akbaba",
"position": "M",
"userCount": 604,
"id": 343527
},
"playerOut": {
"name": "Gedson Fernandes",
"slug": "fernandes-gedson",
"shortName": "G. Fernandes",
"position": "M",
"userCount": 3030,
"id": 862055
},
"id": 120059396,
"time": 71,
"isHome": true,
"incidentType": "substitution"
},
{
"playerIn": {
"name": "Henry Onyekuru",
"slug": "henry-onyekuru",
"shortName": "H. Onyekuru",
"position": "M",
"userCount": 1474,
"id": 809220
},
"playerOut": {
"name": "Emre Kılınç",
"slug": "emre-kilinc",
"shortName": "E. Kılınç",
"position": "M",
"userCount": 526,
"id": 202032
},
"id": 120059398,
"time": 71,
"isHome": true,
"incidentType": "substitution"
},
{
"player": {
"name": "Haris Hajradinović",
"slug": "haris-hajradinovic",
"shortName": "H. Hajradinović",
"position": "M",
"userCount": 357,
"id": 254979
},
"playerName": "Haris Hajradinović",
"reason": "Foul",
"id": 119728581,
"time": 71,
"isHome": false,
"incidentClass": "yellow",
"incidentType": "card"
},
{
"homeScore": 1,
"awayScore": 1,
"player": {
"name": "Isaac Kiese Thelin",
"slug": "isaac-kiese-thelin",
"shortName": "I. K. Thelin",
"position": "F",
"userCount": 386,
"id": 178743
},
"assist1": {
"name": "Haris Hajradinović",
"slug": "haris-hajradinovic",
"shortName": "H. Hajradinović",
"position": "M",
"userCount": 357,
"id": 254979
},
"id": 141786585,
"time": 51,
"isHome": false,
"incidentClass": "regular",
"incidentType": "goal"
},
{
"playerIn": {
"name": "Kevin Varga",
"slug": "kevin-varga",
"shortName": "K. Varga",
"position": "M",
"userCount": 274,
"id": 602730
},
"playerOut": {
"name": "Gilbert Koomson",
"slug": "gilbert-koomson",
"shortName": "G. Koomson",
"position": "F",
"userCount": 76,
"id": 341107
},
"id": 120059401,
"time": 46,
"isHome": false,
"incidentType": "substitution"
},
{
"text": "HT",
"homeScore": 1,
"awayScore": 0,
"isLive": false,
"time": 45,
"addedTime": 999,
"incidentType": "period"
},
{
"player": {
"name": "Isaac Kiese Thelin",
"slug": "isaac-kiese-thelin",
"shortName": "I. K. Thelin",
"position": "F",
"userCount": 386,
"id": 178743
},
"playerName": "Isaac Kiese Thelin",
"reason": "Foul",
"id": 119728580,
"time": 15,
"isHome": false,
"incidentClass": "yellow",
"incidentType": "card"
},
{
"homeScore": 1,
"awayScore": 0,
"player": {
"name": "Muhammed Kerem Aktürkoğlu",
"firstName": "",
"lastName": "",
"slug": "muhammed-kerem-akturkoglu",
"shortName": "M. K. Aktürkoğlu",
"position": "F",
"userCount": 281,
"id": 903324
},
"id": 141786583,
"time": 9,
"isHome": true,
"incidentClass": "regular",
"incidentType": "goal"
}
]
}

ABC = {
"incidents": [
{
"text": "FT",
"homeScore": 2,
"awayScore": 1,
"isLive": False,
"time": 90,
"addedTime": 999,
"incidentType": "period"
},
{
"length": 4,
"time": 90,
"addedTime": 0,
"incidentType": "injuryTime"
},
{
"homeScore": 2,
"awayScore": 1,
"player": {
"name": "Mostafa Mohamed",
"firstName": "",
"lastName": "",
"slug": "mostafa-mohamed",
"shortName": "M. Mohamed",
"position": "F",
"userCount": 3949,
"id": 873551
},
"id": 141786584,
"time": 89,
"isHome": True,
"incidentClass": "penalty",
"incidentType": "goal"
},
{
"player": {
"name": "Duško Tošić",
"slug": "dusko-tosic",
"shortName": "D. Tošić",
"position": "D",
"userCount": 215,
"id": 14557
},
"playerName": "Duško Tošić",
"reason": "Foul",
"id": 119728583,
"time": 85,
"isHome": False,
"incidentClass": "yellow",
"incidentType": "card"
},
{
"playerIn": {
"name": "Younès Belhanda",
"slug": "younes-belhanda",
"shortName": "Y. Belhanda",
"position": "M",
"userCount": 2165,
"id": 72999
},
"playerOut": {
"name": "Martin Linnes",
"slug": "martin-linnes",
"shortName": "M. Linnes",
"position": "D",
"userCount": 339,
"id": 109569
},
"id": 120059400,
"time": 82,
"isHome": True,
"incidentType": "substitution"
},
{
"player": {
"name": "Kevin Varga",
"slug": "kevin-varga",
"shortName": "K. Varga",
"position": "M",
"userCount": 274,
"id": 602730
},
"playerName": "Kevin Varga",
"reason": "Foul",
"id": 119728582,
"time": 82,
"isHome": False,
"incidentClass": "yellow",
"incidentType": "card"
},
{
"playerIn": {
"name": "DeAndre Yedlin",
"slug": "deandre-yedlin",
"shortName": "D. Yedlin",
"position": "D",
"userCount": 702,
"id": 314040
},
"playerOut": {
"name": "Muhammed Kerem Aktürkoğlu",
"firstName": "",
"lastName": "",
"slug": "muhammed-kerem-akturkoglu",
"shortName": "M. K. Aktürkoğlu",
"position": "F",
"userCount": 281,
"id": 903324
},
"id": 120059399,
"time": 77,
"isHome": True,
"incidentType": "substitution"
},
{
"playerIn": {
"name": "Ryan Donk",
"slug": "ryan-donk",
"shortName": "R. Donk",
"position": "D",
"userCount": 489,
"id": 14900
},
"playerOut": {
"name": "Ryan Babel",
"slug": "ryan-babel",
"shortName": "R. Babel",
"position": "F",
"userCount": 1577,
"id": 1876
},
"id": 120059397,
"time": 72,
"isHome": True,
"incidentType": "substitution"
},
{
"playerIn": {
"name": "Emre Akbaba",
"slug": "emre-akbaba",
"shortName": "E. Akbaba",
"position": "M",
"userCount": 604,
"id": 343527
},
"playerOut": {
"name": "Gedson Fernandes",
"slug": "fernandes-gedson",
"shortName": "G. Fernandes",
"position": "M",
"userCount": 3030,
"id": 862055
},
"id": 120059396,
"time": 71,
"isHome": True,
"incidentType": "substitution"
},
{
"playerIn": {
"name": "Henry Onyekuru",
"slug": "henry-onyekuru",
"shortName": "H. Onyekuru",
"position": "M",
"userCount": 1474,
"id": 809220
},
"playerOut": {
"name": "Emre Kılınç",
"slug": "emre-kilinc",
"shortName": "E. Kılınç",
"position": "M",
"userCount": 526,
"id": 202032
},
"id": 120059398,
"time": 71,
"isHome": True,
"incidentType": "substitution"
},
{
"player": {
"name": "Haris Hajradinović",
"slug": "haris-hajradinovic",
"shortName": "H. Hajradinović",
"position": "M",
"userCount": 357,
"id": 254979
},
"playerName": "Haris Hajradinović",
"reason": "Foul",
"id": 119728581,
"time": 71,
"isHome": False,
"incidentClass": "yellow",
"incidentType": "card"
},
{
"homeScore": 1,
"awayScore": 1,
"player": {
"name": "Isaac Kiese Thelin",
"slug": "isaac-kiese-thelin",
"shortName": "I. K. Thelin",
"position": "F",
"userCount": 386,
"id": 178743
},
"assist1": {
"name": "Haris Hajradinović",
"slug": "haris-hajradinovic",
"shortName": "H. Hajradinović",
"position": "M",
"userCount": 357,
"id": 254979
},
"id": 141786585,
"time": 51,
"isHome": False,
"incidentClass": "regular",
"incidentType": "goal"
},
{
"playerIn": {
"name": "Kevin Varga",
"slug": "kevin-varga",
"shortName": "K. Varga",
"position": "M",
"userCount": 274,
"id": 602730
},
"playerOut": {
"name": "Gilbert Koomson",
"slug": "gilbert-koomson",
"shortName": "G. Koomson",
"position": "F",
"userCount": 76,
"id": 341107
},
"id": 120059401,
"time": 46,
"isHome": False,
"incidentType": "substitution"
},
{
"text": "HT",
"homeScore": 1,
"awayScore": 0,
"isLive": False,
"time": 45,
"addedTime": 999,
"incidentType": "period"
},
{
"player": {
"name": "Isaac Kiese Thelin",
"slug": "isaac-kiese-thelin",
"shortName": "I. K. Thelin",
"position": "F",
"userCount": 386,
"id": 178743
},
"playerName": "Isaac Kiese Thelin",
"reason": "Foul",
"id": 119728580,
"time": 15,
"isHome": False,
"incidentClass": "yellow",
"incidentType": "card"
},
{
"homeScore": 1,
"awayScore": 0,
"player": {
"name": "Muhammed Kerem Aktürkoğlu",
"firstName": "",
"lastName": "",
"slug": "muhammed-kerem-akturkoglu",
"shortName": "M. K. Aktürkoğlu",
"position": "F",
"userCount": 281,
"id": 903324
},
"id": 141786583,
"time": 9,
"isHome": True,
"incidentClass": "regular",
"incidentType": "goal"
}
]
}
First, create a dictionary to hold all distinct incidentType. Then iterate through incidents and check if whether incidentType exists in the dictionary or not. If it exists? Append. if not, create a new key : value pair
result = {}
for js in ABC["incidents"]:
icdType = js["incidentType"]
if icdType in result:
result[icdType].append(js)
else:
result[icdType] = [js]
for key,val in result.items():
print(key, ":", val, "\n")

Converting dataframe containing columns data type to json showing some encoded variables

I have below dataframe(df):
Index col1 col2 col3
data_type object float64 float64
record_count 20 20 30
Percentage 10 8 5
When I am converting this dataframe into json, i got the below json file:
df.to_json()
"col1": {
"data_type": {
"alignment": 8,
"byteorder": "=",
"descr": [
[
"",
"<f8"
]
],
"flags": 0,
"isalignedstruct": false,
"isnative": true,
"kind": "o",
"name": "object",
"num": 12,
"str": "<f8"
}
"record_count": 20,
"Percentage" :10
}
"col2": {
"data_type": {
"alignment": 8,
"byteorder": "=",
"descr": [
[
"",
"<f8"
]
],
"flags": 0,
"isalignedstruct": false,
"isnative": true,
"kind": "f",
"name": "float64",
"num": 12,
"str": "<f8"
}
"record_count": 20,
"Percentage" :8
},
"col3": {
"data_type": {
"alignment": 8,
"byteorder": "=",
"descr": [
[
"",
"<f8"
]
],
"flags": 0,
"isalignedstruct": false,
"isnative": true,
"kind": "f",
"name": "float64",
"num": 12,
"str": "<f8"
}
"record_count": 30,
"Percentage" :5
}
I want to extract only data_type like below:
"col1": {
"data_type": "float64",
"record_count":'20',
"Percentage" : 10
}
I have similar rows with different integer as well as string values, I am able to extract them as it is, but for data_type I am getting unknown characters after converting to json.

Get names of keys in objectpath

How would I get the names of the keys, for example [800, 801] (the key names are unknown) with objectpath.
It is easy in jmespath: keys(#).
"groups": {
"800": {
"short_name": "22",
"oname": "11",
"group": 8,
"title": "SS",
"name": "33",
"onames": [""],
"alt_name": False,
"waytype": 1,
"multiple": 1,
"primary": 1
},
"801": {
"short_name": "ss",
"oname": "zz",
"group": 8,
"title": "ss",
"name": "bbb",
"onames": [""],
"alt_name": False,
"waytype": 1,
"multiple": 1,
"primary": 0
},

let your object is assigned to name variable
const name = { "groups": {
"800": {
"short_name": "22",
"oname": "11",
"group": 8,
"title": "SS",
"name": "33",
"onames": [""],
"alt_name": false,
"waytype": 1,
"multiple": 1,
"primary": 1
},
"801": {
"short_name": "ss",
"oname": "zz",
"group": 8,
"title": "ss",
"name": "bbb",
"onames": [""],
"alt_name": false,
"waytype": 1,
"multiple": 1,
"primary": 0
} } }
Use for loop to get the key name as
for(var num in name.groups) {
console.log(num);
}
and to get the values of key
for(var num in name.groups) {
console.log(name.groups[num]);
}

Python/PySpark parse JSON string with numbered attributes

I need to store JSON strings like the one below in some file format different from plaintext (e.g: parquet):
{
"vidName": "Foo",
"vidInfo.0.size.length": 10,
"vidInfo.0.size.width": 10,
"vidInfo.0.quality": "Good",
"vidInfo.1.size.length": 7,
"vidInfo.1.size.width": 3,
"vidInfo.1.quality": "Bad",
"vidInfo.2.size.length": 10,
"vidInfo.2.size.width": 2,
"vidInfo.2.quality": "Excelent"
}
There's no known bound for the index of vidInfo (can be 10, 20). Thus I want either to have vidInfos in an array, or explode such JSON object into multiple smaller objects.
I found this question: PHP JSON parsing (number attributes?)
But it is in PHP which I do not quite understand. And I am not sure whether it is same as what I need.
The intermediate data should be something like this:
{
"vidName": "Foo",
"vidInfo": [
{
"id": 0,
"size": {
"length": 10,
"width": 10
},
"quality": "Good"
},
{
"id": 1,
"size": {
"length": 7,
"width": 3
},
"quality": "Bad"
},
{
"id": 2,
"size": {
"length": 10,
"width": 2
},
"quality": "Excelent"
}
]
}
or like this:
{
"vidName": "Foo",
"vidInfo": [
{
"size": {
"length": 10,
"width": 10
},
"quality": "Good"
},
{
"size": {
"length": 7,
"width": 3
},
"quality": "Bad"
},
{
"size": {
"length": 10,
"width": 2
},
"quality": "Excelent"
}
]
}
I am stuck, and would need some hints to move on.
Could you please help?
Thanks a lot for your help.

I found this library https://github.com/amirziai/flatten which does the trick.
In [154]: some_json = {
...: "vidName": "Foo",
...: "vidInfo.0.size.length": 10,
...: "vidInfo.0.size.width": 10,
...: "vidInfo.0.quality": "Good",
...: "vidInfo.1.size.length": 7,
...: "vidInfo.1.size.width": 3,
...: "vidInfo.1.quality": "Bad",
...: "vidInfo.2.size.length": 10,
...: "vidInfo.2.size.width": 2,
...: "vidInfo.2.quality": "Excelent"
...: }
In [155]: some_json
Out[155]:
{'vidName': 'Foo',
'vidInfo.0.size.length': 10,
'vidInfo.0.size.width': 10,
'vidInfo.0.quality': 'Good',
'vidInfo.1.size.length': 7,
'vidInfo.1.size.width': 3,
'vidInfo.1.quality': 'Bad',
'vidInfo.2.size.length': 10,
'vidInfo.2.size.width': 2,
'vidInfo.2.quality': 'Excelent'}
In [156]: from flatten_json import unflatten_list
...: import json
...: nested_json = unflatten_list(json.loads(json.dumps(some_json)), '.')
In [157]: nested_json
Out[157]:
{'vidInfo': [{'quality': 'Good', 'size': {'length': 10, 'width': 10}},
{'quality': 'Bad', 'size': {'length': 7, 'width': 3}},
{'quality': 'Excelent', 'size': {'length': 10, 'width': 2}}],
'vidName': 'Foo'}

How to Convert a list of dicts into nested JSON in python without using pandas DataFrame

I have a list of dicts like this
[
{
"subject_id": 1,
"subject_name": "HR Sector 0",
"id": 1,
"name": "parent2",
"value": 10.6
},
{
"subject_id": 18,
"subject_name": "Test11",
"id": 1,
"name": "parent2",
"value": 12
},
{
"subject_id": 2,
"subject_name": "AG1",
"id": 2,
"name": "Customer Delivery Dpt. 1",
"value": 17
},
{
"subject_id": 3,
"subject_name": "Finance Group 2",
"id": 2,
"name": "Customer Delivery Dpt. 1",
"value": 1.5
},
{
"subject_id": 10,
"subject_name": "test",
"id": 2,
"name": "Customer Delivery Dpt. 1",
"value": 10
},
{
"subject_id": null,
"subject_name": null,
"id": 3,
"name": "Technology Team 2",
"value": null
},
{
"subject_id": 8,
"subject_name": "Group 4",
"id": 5,
"name": "Accounting Group 4",
"value": 10
},
{
"subject_id": null,
"subject_name": null,
"id": 9,
"name": "PG2",
"value": null
}
]
I want to convert it into nested JSON and ignore null values to get below result set
[
{
"id": 1,
"name": "parent2",
"subjects”: [
{”subject_id": 1,
"subject_name": "HR Sector 0",
"value": 10.6
},
{”subject_id": 18,
"subject_name": "Test11",
"value": 12
}
]
},
{
"id": 2,
"name": "Customer Delivery Dpt. 1",
"subjects”: [
{“subject_id": 2,
"subject_name": "AG1",
"value": 17
},
{“subject_id": 3,
"subject_name": "Finance Group 2",
"value": 1.5
},
{“subject_id": 10,
"subject_name": “test”,
"value": 10
}
]
},
{
"id": 3,
"name": "Technology Team 2",
"subjects”: []
},
{
"id": 5,
"name": "Accounting Group 4",
"subjects” : [
{ "subject_id": 8,
"subject_name": "Group 4",
"value": 10
}
]
},
{
"id": 9,
"name": "PG2",
"subjects”: []
}
]

import json
arr = [
{
"subject_id": 1,
"subject_name": "HR Sector 0",
"id": 1,
"name": "parent2",
"value": 10.6
},
{
"subject_id": 18,
"subject_name": "Test11",
"id": 1,
"name": "parent2",
"value": 12
},
{
"subject_id": 2,
"subject_name": "AG1",
"id": 2,
"name": "Customer Delivery Dpt. 1",
"value": 17
},
{
"subject_id": 3,
"subject_name": "Finance Group 2",
"id": 2,
"name": "Customer Delivery Dpt. 1",
"value": 1.5
},
{
"subject_id": 10,
"subject_name": "test",
"id": 2,
"name": "Customer Delivery Dpt. 1",
"value": 10
},
{
"subject_id": None,
"subject_name": None,
"id": 3,
"name": "Technology Team 2",
"value": None
},
{
"subject_id": 8,
"subject_name": "Group 4",
"id": 5,
"name": "Accounting Group 4",
"value": 10
},
{
"subject_id": None,
"subject_name": None,
"id": 9,
"name": "PG2",
"value": None
}
]
def process_arr_to_json(arr):
newArr = []
addedIds = {}
for item in arr:
if(addedIds.get(item["id"]) is None):
formatted_item = {"subjects":[]}
newArr.append(formatted_item)
addedIds[item["id"]] = {"idx": 0, "pos": len(newArr)-1} #index in the dictionary for the subject item
else:
formatted_item = newArr[addedIds[item["id"]]["pos"]]
addedIds[item["id"]]["idx"] += 1
for k,v in item.items():
if(v is not None):
if(k == "id" or k == "name"):
formatted_item[k] = v
else:
if(len(formatted_item["subjects"]) <= addedIds[item["id"]]["idx"]):
formatted_item["subjects"].append({k:v})
else:
formatted_item["subjects"][addedIds[item["id"]]["idx"]][k] = v
print(newArr)
return json.dumps(newArr)
if __name__ == "__main__":
process_arr_to_json(arr)
my solution

Please see code below to form the merged results
import json
def process_items(items):
results = {}
for item in items:
results[item['id']] = {
'id': item['id'],
'name': item['name'],
}
to_append = {}
for k in ['subject_id', 'value', 'subject_name']:
if item.get(k):
to_append[k] = item[k]
results[item['id']].setdefault('subjects', [])
if to_append:
results[item['id']]['subjects'].append(to_append)
return results
items = [
{
"subject_id": 1,
"subject_name": "HR Sector 0",
"id": 1,
"name": "parent2",
"value": 10.6
},
{
"subject_id": 18,
"subject_name": "Test11",
"id": 1,
"name": "parent2",
"value": 12
},
{
"subject_id": 2,
"subject_name": "AG1",
"id": 2,
"name": "Customer Delivery Dpt. 1",
"value": 17
},
{
"subject_id": 3,
"subject_name": "Finance Group 2",
"id": 2,
"name": "Customer Delivery Dpt. 1",
"value": 1.5
},
{
"subject_id": 10,
"subject_name": "test",
"id": 2,
"name": "Customer Delivery Dpt. 1",
"value": 10
},
{
"subject_id": None,
"subject_name": None,
"id": 3,
"name": "Technology Team 2",
"value": None
},
{
"subject_id": 8,
"subject_name": "Group 4",
"id": 5,
"name": "Accounting Group 4",
"value": 10
},
{
"subject_id": None,
"subject_name": None,
"id": 9,
"name": "PG2",
"value": None
}
]
result = process_items(items)
json.dumps(result.values()) # For python 3: json.dumps(list(results.values()))

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