Convert Table into an array in matlab - arrays

I want to convert a table into array.
I've written the following code but it's generating an error.
T2 = table2array('Testing_data');
Following is my dataset:
Any help is appreciated. Thank you.

Related

How can I parse JSON arrays in postgresql?

I am using PostgreSQL 9.5.14, and have a column in a table that contains JSON arrays that I need to parse for their contents.
Using a select I can see that the structure of the JSON is of this kind:
SELECT rule_results from table limit 5;
Result:
[{"rule_key":"applicant_not_lived_outside_eu"},{"rule_key":"family_assets_exceed_limit"},{"rule_key":"owned_a_deed"}]
[]
[]
[{"rule_key":"family_category","details":"apply_with_parents_under_25"}]
[]
I have been unable to create an SQL command to give me the values of the rule_key keys.
I've attempted to use the documentation for json-functions in postgresql to find a solution from
https://www.postgresql.org/docs/9.5/functions-json.html
SELECT rule_results::json->'rule_key' as results from table;
This gives me null values only.
SELECT jsonb_object_keys(rule_results::jsonb) from table;
This results in the error msg "cannot call jsonb_object_keys on a scalar", which seems to mean that the query is limited to a single row.
This looks simple enough, an array with key:value pairs, but somehow the answer eludes me. I would appreciate any help.

demo: db<>fiddle
Different solutions are possible. It depends on what you are expecting finally. But all solutions would use the function json_array_elements(). This expands every element into one row. With that you can do whatever you want.
This results in one row per value:
SELECT
value -> 'rule_key'
FROM
data,
json_array_elements(rule_results)

How to read data to an array without ''

I was trying to read a data file to an array which include float and string.
metadata = genfromtxt('iris_labels.tsv',delimiter='\t', dtype=str)
print(metadata)
Which give me
is that possible to ignore the ('') sign?

Not a numpy expert and I haven't tried it out but I think you're looking for something like
my_dtype=np.dtype([
('petal.w', np.float),
('petal.h', np.float),
('sepal.w', np.float),
('sepal.h', np.float),
('species', 'a32')
])
p.s. I don't know the actual order of your columns

How to insert data in codename one db using prepared statement?

I am trying to use to insert into the table but got the exception that array index out of bounds ?
Please give me the idea how to do that and where is I am making mistake?
I have tried many conversion but doesn't get succeeded.
Following is the code
Object[]param={ID,name,Fathername,Address,Mob,Gender,Qualification};
try{
db=Display.getInstance().openOrCreate("students.db");
db.execute("insert into clStudent values('?','?','?',?,'?','?','?')", (Object[]) param) ;

You should drop the single quotes around the question marks in your query string.

Importing jSON Array into Hive/Hadoop

I'm using the HortonWorks Hadoop Sandbox and I have imported a jSON string into a table, as per this guide however I run into trouble as my string contains an array which is not handled well by json_tuple(). I have tried the expolode() function, but that returns the following error:
"Error occurred executing hive query: OK FAILED: UDFArgumentException explode() takes an array or a map as a parameter"
What does that mean exactly and how can I fix it? Would the problem be with the format of the table? I just followed as per the guide above and created the table with:
CREATE EXTERNAL TABLE games
(
value STRING
)
LOCATION '/user/hue/games'
The value I am trying to explode is an array like this:
[{"gameId":49927894,"invalid":false,"gameMode":"CLASSIC","gameType":"MATCHED_GAME","subType":"RANKED_SOLO_5x5","mapId":1,"teamId":100,"championId":53,"spell1":4,"spell2":14,"level":30,"ipEarned":228,"createDate":1404215396001,"fellowPlayers":[{"summonerId":305443,"teamId":200,"championId":62},{"summonerId":468080,"teamId":100,"championId":23},{"summonerId":356814,"teamId":100,"championId":64},{"summonerId":279828,"teamId":200,"championId":222},{"summonerId":284016,"teamId":100,"championId":112},{"summonerId":222776,"teamId":200,"championId":37},{"summonerId":380226,"teamId":100,"championId":104},{"summonerId":871165,"teamId":200,"championId":238},{"summonerId":443896,"teamId":200,"championId":102}],"stats":{"level":12,"goldEarned":7829,"numDeaths":2,"barracksKilled":1,"minionsKilled":15,"championsKilled":2,"goldSpent":6755,"totalDamageDealt":21181,"totalDamageTaken":10271,"team":100,"win":true,"largestMultiKill":1,"physicalDamageDealtPlayer":8258,"magicDamageDealtPlayer":12390,"physicalDamageTaken":7603,"magicDamageTaken":2215,"timePlayed":1560,"totalHeal":782,"totalUnitsHealed":1,"assists":7,"item0":3069,"item1":3024,"item2":2045,"item3":3117,"item4":3082,"item6":3341,"visionWardsBought":1,"magicDamageDealtToChampions":3193,"physicalDamageDealtToChampions":1144,"totalDamageDealtToChampions":4870,"trueDamageDealtPlayer":532,"trueDamageDealtToChampions":532,"trueDamageTaken":451,"wardKilled":2,"wardPlaced":12,"totalTimeCrowdControlDealt":36}},{"gameId":49921219,"invalid":false,"gameMode":"CLASSIC","gameType":"MATCHED_GAME","subType":"RANKED_SOLO_5x5","mapId":1,"teamId":100,"championId":72,"spell1":4,"spell2":11,"level":30,"ipEarned":71,"createDate":1404210159007,"fellowPlayers":[{"summonerId":323330,"teamId":100,"championId":102},{"summonerId":430227,"teamId":200,"championId":134},{"summonerId":1403590,"teamId":200,"championId":114},{"summonerId":382370,"teamId":100,"championId":99},{"summonerId":445767,"teamId":100,"championId":51},{"summonerId":490295,"teamId":200,"championId":19},{"summonerId":313523,"teamId":100,"championId":4},{"summonerId":308769,"teamId":200,"championId":25},{"summonerId":1591549,"teamId":200,"championId":67}],"stats":{"level":16,"goldEarned":12337,"numDeaths":5,"minionsKilled":60,"championsKilled":4,"goldSpent":11955,"totalDamageDealt":128541,"totalDamageTaken":37539,"killingSprees":1,"largestKillingSpree":2,"team":100,"win":false,"neutralMinionsKilled":84,"largestMultiKill":1,"physicalDamageDealtPlayer":68670,"magicDamageDealtPlayer":40557,"physicalDamageTaken":25561,"magicDamageTaken":8767,"timePlayed":2354,"totalHeal":4024,"totalUnitsHealed":1,"assists":12,"item0":3143,"item1":3102,"item2":2045,"item3":3283,"item4":3207,"item6":3364,"visionWardsBought":2,"magicDamageDealtToChampions":3449,"physicalDamageDealtToChampions":3735,"totalDamageDealtToChampions":7690,"trueDamageDealtPlayer":19313,"trueDamageDealtToChampions":505,"trueDamageTaken":3209,"wardKilled":3,"wardPlaced":5,"neutralMinionsKilledEnemyJungle":7,"neutralMinionsKilledYourJungle":77,"totalTimeCrowdControlDealt":1290}},{"gameId":49846672,"invalid":false,"gameMode":"CLASSIC","gameType":"MATCHED_GAME","subType":"RANKED_SOLO_5x5","mapId":1,"teamId":100,"championId":72,"spell1":4,"spell2":11,"level":30,"ipEarned":92,"createDate":1404137990304,"fellowPlayers":[{"summonerId":390284,"teamId":100,"championId":29},{"summonerId":333970,"teamId":200,"championId":236},{"summonerId":306968,"teamId":200,"championId":157},{"summonerId":275006,"teamId":200,"championId":84},{"summonerId":271369,"teamId":200,"championId":92},{"summonerId":942667,"teamId":100,"championId":68},{"summonerId":475293,"teamId":100,"championId":201},{"summonerId":560185,"teamId":100,"championId":115},{"summonerId":340177,"teamId":200,"championId":54}],"stats":{"level":18,"goldEarned":14683,"numDeaths":3,"barracksKilled":1,"turretsKilled":2,"minionsKilled":33,"championsKilled":10,"goldSpent":13153,"totalDamageDealt":146399,"totalDamageTaken":29156,"doubleKills":1,"killingSprees":1,"largestKillingSpree":9,"team":100,"win":true,"neutralMinionsKilled":86,"largestMultiKill":2,"physicalDamageDealtPlayer":85905,"magicDamageDealtPlayer":42140,"physicalDamageTaken":25170,"magicDamageTaken":2669,"largestCriticalStrike":349,"timePlayed":1932,"totalHeal":4997,"totalUnitsHealed":1,"assists":19,"item0":3143,"item1":3207,"item2":3211,"item3":3078,"item4":3009,"item5":1028,"item6":3340,"visionWardsBought":2,"magicDamageDealtToChampions":4955,"physicalDamageDealtToChampions":6923,"totalDamageDealtToChampions":12270,"trueDamageDealtPlayer":18353,"trueDamageDealtToChampions":391,"trueDamageTaken":1317,"wardKilled":3,"wardPlaced":7,"neutralMinionsKilledEnemyJungle":6,"neutralMinionsKilledYourJungle":80,"totalTimeCrowdControlDealt":879}},{"gameId":49842237,"invalid":false,"gameMode":"CLASSIC","gameType":"MATCHED_GAME","subType":"RANKED_SOLO_5x5","mapId":1,"teamId":200,"championId":72,"spell1":4,"spell2":11,"level":30,"ipEarned":239,"createDate":1404132909924,"fellowPlayers":[{"summ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Any help very much appreciated!

The explode() hive function takes a hive array or map, and you gave it a String value. json_tuple() worked in the guide because it made your string into a map.
You'll want to convert your json array into a format that hive can accept, or use one of the JSON SerDes or something of that nature in order to query the way you want.
JSON SerDe for Hive that supports JSON arrays

Removing duplicate entries of cell array MATLAB

I am facing a problem. i have a huge data file in text format and the entries are in this format:
18 1 1471-213X-6-54-12 503 5.333333e-001 xyz
the First column range from 1-22 and first column and third column must not be duplicated. If duplicated values exists i want to remove them. I am working in Matlab.
I could not find any suitable stuff to solve this problem.
Anybody hint/help will highly be appreciated.
Thanks in advance.
Mehdi

Here is a hint, suppose your first column is called f, and your third colum is called t.
you may be interested in the following commands:
[xxx,IA_f] = unique(f)
[xxx,IA_t] = unique(t)
[xxx,IA_tf] = unique([f t], 'rows')
Assuming that your data is in matrix'M' and you have selected IA as the proper index, you can do:
M_unique = M(IA,:)

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