I'm trying to import some facebook data into spreadsheets.
The request
https://graph.facebook.com/v2.6/{user id}?fields=name&access_token=1{my token}
Gets me
{
"name": "user",
"id": "numeric id"
}
When I import it to spreadsheets with:
=IMPORTDATA(https://graph.facebook.com/v2.6/{user id}?access_token={my token}
)
On the cells, I get {"name": "user" in one cell and "id": "numeric id" in another. But I only need the "name" value, How can I target just that value, in only one cell as I have no use for the second value.
Since you want only one cell from the imported range, which happens to be its upper left corner, the array_constrain function can help:
=array_constrain(importdata("..."), 1, 1)
Generally, the 2nd and 3rd arguments of array_constrain determine how many rows and how many columns you want to keep.
You can also get rid of "name": at the beginning by using the text processing functions such as left, right, regexreplace, etc. For example, wrapping the previous formula in
=regexreplace( ... , "^\S+: |""", "")
will get rid of "name": and of the quote marks around the name.
Related
I am geocoding using OpenRefine. I pulled data from OpenStreetMaps to my datasetstructure of data
I am adding a "column based on this column" for the coordinates.I want to check that the display_name contains "Rheinland-Pfalz" and if it does, I want to extract the latitude and longitude,i.e. pair.lat + ',' + pair.lon. I want to do this iteratively but I don't know how. I have tried the following:
if(display_name[0].contains("Rheinland-Pfalz"), with(value.parseJson()[0], pair, pair.lat + ',' + pair.lon),"nothing")
but I want to do this for each index [0] up to however many there are. I would appreciate if anyone could help.
Edit: Thanks for your answer b2m.
How would I extract the display_name corresponding to the coordinates that we get. I want the output to be display_name lat,lon for each match (i.e. contains "Rheinland-Pfalz", because I have a different column containing a piece of string that I want to match with the matches generated already.
For example, using b2m's code and incorporating the display_name in the output we get 2 matches:
Schaumburg, Balduinstein, Diez, Rhein-Lahn-Kreis, Rheinland-Pfalz, Deutschland 50.33948155,7.9784308849342604
Schaumburg, Horhausen, Flammersfeld, Landkreis Altenkirchen, Rheinland-Pfalz, Deutschland 52.622319,14.5865283
For each row, I have another string in a different column. Here the entry is "Rhein-Lahn-Kreis". I want to filter the two matches above to only keep those containing my string in the other column. In this case "Rhein-Lahn-Kreis" but the other column entry is different for each row. I hope this is clear and I would greatly appreciate any help
Assuming we have the following json data
[
{"display_name": "BW", "lat": 0, "lon": 1},
{"display_name": "NRW 1", "lat": 2, "long": 3},
{"display_name": "NRW 2", "lat": 4, "lon": 5}
]
You can extract the combined elements lat and long with forEach and filter using the following GREL expression e.g. in the Add column based on this column dialog.
forEach(
filter(
value.parseJson(), geodata, geodata.display_name.contains("NRW")
), el, el.lat + "," + el.lon)
.join(";")
This will result in a new field with the value 2,3;4,5.
You can then split the new multi valued field on the semicolon ";" to obtain separated values (2,3 and 4,5).
Another approach would be to split the JSON Array elements into separate rows, avoiding the forEach and filter functions.
I'm searching through the documentation as best I can, I'm just on a time limit here so if someone can tell me that would be great.
I need to insert data into a column and have it push the data in the column down when it's inserted. For example I need to add the word "Good" at the top of the column, "Bad" WAS at the top, but when I pushed in "Good", "Bad" became the number two spot, the number two spot became the number three spot, etc. It needs to do this without deleting or moving the rows themselves because I'm reading data from two columns in the sheet and then writing to a third column.
Thanks in advance!
Welcome to StackOverflow.
From what I understood reading your question is that you have already been able to read data from two column and now you just want to store some of them in a separate column. Apologies if I misunderstood your question.
If I understood your question right, I would suggest you to create a list of the requests and make a batch update of it. Which would help you refraining yourself from reaching the write quota.
So, here how it goes-
request = []
request.append({
"updateCells": {
"rows": [
{
"values":[
{
"userEnteredValue": {
"numberValue": 546564 #Assuming your value is integer
},
"userEnteredFormat": {
"horizontalAlignment": "CENTER",
"verticalAlignment": "MIDDLE"
}
}
]
}
],
"fields": "*",
"range": {
#Replace these values with actual values
"sheetId": sheetId,
"startRowIndex": startRow, #Indexing start from 0
"endRowIndex": endRow,
"startColumnIndex": startColumn,
"endColumnIndex": endColumn,
}
}
})
#You can add more requests like this in the list and then execute
body = {
"requests": request
}
response = sheet.spreadsheets().batchUpdate(
spreadsheetId=spreadsheet_id,
body=body).execute()
#If you are using gspread, then you can use this
sheet.batch_update({"requests" : request})
This will update the cells with your given value. For detailed information and other formatting follow the documentation.
I'm getting Yahoo Finance data as a JSON file (via the YahooFinancials python API) and I would like to be able to parse the data in a smart way to feed my Google Sheet.
For this example, I'm interested in getting the "cash" variable under the "date" nested structure. But as you'll see, sometimes there is no "cash" variable under the first date, so I would like the script/formula to go and get the "cash" variable that's under the second date structure.
Here is sample 1 of JSON code:
{ "balanceSheetHistoryQuarterly": {
"ABBV": [
{
"2018-12-31": {
"totalStockholderEquity": -2921000000,
"netTangibleAssets": -45264000000
}
},
{
"2018-09-30": {
"intangibleAssets": 26625000000,
"capitalSurplus": 14680000000,
"totalLiab": 69085000000,
"totalStockholderEquity": -2921000000,
"otherCurrentLiab": 378000000,
"totalAssets": 66164000000,
"commonStock": 18000000,
"otherCurrentAssets": 112000000,
"retainedEarnings": 6789000000,
"otherLiab": 16511000000,
"goodWill": 15718000000,
"treasuryStock": -24408000000,
"otherAssets": 943000000,
"cash": 8015000000,
"totalCurrentLiabilities": 15387000000,
"shortLongTermDebt": 1026000000,
"otherStockholderEquity": -2559000000,
"propertyPlantEquipment": 2950000000,
"totalCurrentAssets": 18465000000,
"longTermInvestments": 1463000000,
"netTangibleAssets": -45264000000,
"shortTermInvestments": 770000000,
"netReceivables": 5780000000,
"longTermDebt": 37187000000,
"inventory": 1786000000,
"accountsPayable": 10981000000
}
},
{
"2018-06-30": {
"intangibleAssets": 26903000000,
"capitalSurplus": 14596000000,
"totalLiab": 65016000000,
"totalStockholderEquity": -3375000000,
"otherCurrentLiab": 350000000,
"totalAssets": 61641000000,
"commonStock": 18000000,
"otherCurrentAssets": 128000000,
"retainedEarnings": 5495000000,
"otherLiab": 16576000000,
"goodWill": 15692000000,
"treasuryStock": -23484000000,
"otherAssets": 909000000,
"cash": 3547000000,
"totalCurrentLiabilities": 17224000000,
"shortLongTermDebt": 3026000000,
"otherStockholderEquity": -2639000000,
"propertyPlantEquipment": 2787000000,
"totalCurrentAssets": 13845000000,
"longTermInvestments": 1505000000,
"netTangibleAssets": -45970000000,
"shortTermInvestments": 196000000,
"netReceivables": 5793000000,
"longTermDebt": 31216000000,
"inventory": 1580000000,
"accountsPayable": 10337000000
}
},
{
"2018-03-31": {
"intangibleAssets": 27230000000,
"capitalSurplus": 14519000000,
"totalLiab": 65789000000,
"totalStockholderEquity": 3553000000,
"otherCurrentLiab": 125000000,
"totalAssets": 69342000000,
"commonStock": 18000000,
"otherCurrentAssets": 17000000,
"retainedEarnings": 4977000000,
"otherLiab": 17250000000,
"goodWill": 15880000000,
"treasuryStock": -15961000000,
"otherAssets": 903000000,
"cash": 9007000000,
"totalCurrentLiabilities": 17058000000,
"shortLongTermDebt": 6024000000,
"otherStockholderEquity": -2630000000,
"propertyPlantEquipment": 2828000000,
"totalCurrentAssets": 20444000000,
"longTermInvestments": 2057000000,
"netTangibleAssets": -39557000000,
"shortTermInvestments": 467000000,
"netReceivables": 5841000000,
"longTermDebt": 31481000000,
"inventory": 1738000000,
"accountsPayable": 10542000000
}
}
]
}
}
The first date structure (under 2018-12-31) doesn't contain the cash variable. So I would like the Google sheet to go and search for the same data in 2018-09-30 and if not available go and search in 2018-06-30.
OR just scan the nested structure dates and fetch the first "cash" occurrence that will be found.
Basically, I would like to know how to skip the name of the date variable (i.e.2018-12-31) as it doesn't really matter, and just make the formula seek for the first available "cash" variable.
Main questions recap
How to skip mentioning an exact nested level name and scan what's
inside?
How to keep scanning until you find the desired variable with
a value that is not "null" (this can happen)?
What would be the entire formula to achieve the following logic: Scan the JSON file until you find the value > if no value found, fallback to this IMPORTXML function that calls an external API.
Let me know if you need more context about the issue and thanks in advance for your help :)
EDIT: this is the IMPORTJSON formula I use in the cell of the spreadsheet right now.
=ImportJSON("https://api.myjson.com/bins/8mxvi", "/financial/balanceSheetHistoryQuarterly/ABBV/2018-31-12/cash", "noHeaders")
Obviously, this one returns an error as there is nothing under that date. The JSON is also the valid link I use just now.
=REGEXEXTRACT(FILTER(
TRANSPOSE(SPLIT(SUBSTITUTE(A1, ","&CHAR(10), "×"), "×")),
ISNUMBER(SEARCH("*"&"cash"&"*",
TRANSPOSE(SPLIT(SUBSTITUTE(A1, ","&CHAR(10), "×"), "×"))))), ": (.+)")
=INDEX(ARRAYFORMULA(SUBSTITUTE(REGEXEXTRACT(FILTER(TRANSPOSE(SPLIT(SUBSTITUTE(
TRANSPOSE(IMPORTDATA("https://api.myjson.com/bins/8mxvi")), ","&CHAR(10), "×"), "×")),
ISNUMBER(SEARCH("*"&"cash"&"*", TRANSPOSE(SPLIT(SUBSTITUTE(
TRANSPOSE(IMPORTDATA("https://api.myjson.com/bins/8mxvi")), ","&CHAR(10), "×"), "×"))))),
":(.+)"), ",", "")), 1, 1)
Working with the repeating grids through the form builder.
I have a custom control that has a string value represented in json.
{
"data": {
"type": "File",
"itemID": "12345",
"name": "Annual Summary",
"parentFolderID": "fileID",
"owner": "Owner",
"lastModifiedDate": "2016-10-17 22:48:05Z"
}
}
In the controls outside of the repeating grid, i need to check if name = "Annual Summary"
Previously, i had a drop down control and using Calculated Value $dropdownControl = "Annual Summary" it was able to return true if any of the repeated rows contained the value. My understanding is that using the = operator, it will validate against all rows.
Now with the json output of the control, I am attempting to use
contains($jsonStringValue, 'Annual Summary')
However, this only works with one entry and will be null if there are multiple rows.
2 questions:
How would validate whether "Annual Summary" (or any other text) is present within any of the repeated rows?
Is there any way to navigate the json or parse it to XML and navigate it?
Constraint:
within the Calculated Value or Visibility fields within form builder
manipulating the source that is generated by the form builder
You probably want to parse the JSON string first. See also this other Stackoverflow question.
Until Orbeon Forms 2016.3 is released, you would write:
(
for $v in $jsonStringValue
return converter:jsonStringToXml($v)
)//name = 'Annual Summary'
With the above, you also need to scope the namespace:
xmlns:converter="org.orbeon.oxf.json.Converter"
Once Orbeon Forms 2016.3 is released you can switch to:
$jsonStringValue/xxf:json-to-xml()//name = 'Annual Summary'
I am trying to learn mongodb. Suppose there are two tables and they are related. For example like this -
1st table has
First name- Fred, last name- Zhang, age- 20, id- s1234
2nd table has
id- s1234, course- COSC2406, semester- 1
id- s1234, course- COSC1127, semester- 1
id- s1234, course- COSC2110, semester- 1
how to insert data in the mongo db? I wrote it like this, not sure is it correct or not -
db.users.insert({
given_name: 'Fred',
family_name: 'Zhang',
Age: 20,
student_number: 's1234',
Course: ['COSC2406', 'COSC1127', 'COSC2110'],
Semester: 1
});
Thank you in advance
This would be a assuming that what you want to model has the "student_number" and the "Semester" as what is basically a unique identifier for the entries. But there would be a way to do this without accumulating the array contents in code.
You can make use of the upsert functionality in the .update() method, with the help of of few other operators in the statement.
I am going to assume you are going this inside a loop of sorts, so everything on the right side values is actually a variable:
db.users.update(
{
"student_number": student_number,
"Semester": semester
},
{
"$setOnInsert": {
"given_name": given_name,
"family_name": family_name,
"Age": age
},
"$addToSet": { "courses": course }
},
{ "upsert": true }
)
What this does in an "upsert" operation is first looks for a document that may exist in your collection that matches the query criteria given. In this case a "student_number" with the current "Semester" value.
When that match is found, the document is merely "updated". So what is being done here is using the $addToSet operator in order to "update" only unique values into the "courses" array element. This would seem to make sense to have unique courses but if that is not your case then of course you can simply use the $push operator instead. So that is the operation you want to happen every time, whether the document was "matched" or not.
In the case where no "matching" document is found, a new document will then be inserted into the collection. This is where the $setOnInsert operator comes in.
So the point of that section is that it will only be called when a new document is created as there is no need to update those fields with the same information every time. In addition to this, the fields you specified in the query criteria have explicit values, so the behavior of the "upsert" is to automatically create those fields with those values in the newly created document.
After a new document is created, then the next "upsert" statement that uses the same criteria will of course only "update" the now existing document, and as such only your new course information would be added.
Overall working like this allows you to "pre-join" the two tables from your source with an appropriate query. Then you are just looping the results without needing to write code for trying to group the correct entries together and simply letting MongoDB do the accumulation work for you.
Of course you can always just write the code to do this yourself and it would result in fewer "trips" to the database in order to insert your already accumulated records if that would suit your needs.
As a final note, though it does require some additional complexity, you can get better performance out of the operation as shown by using the newly introduced "batch updates" functionality.For this your MongoDB server version will need to be 2.6 or higher. But that is one way of still reducing the logic while maintaining fewer actual "over the wire" writes to the database.
You can either have two separate collections - one with student details and other with courses and link them with "id".
Else you can have a single document with courses as inner document in form of array as below:
{
"FirstName": "Fred",
"LastName": "Zhang",
"age": 20,
"id": "s1234",
"Courses": [
{
"courseId": "COSC2406",
"semester": 1
},
{
"courseId": "COSC1127",
"semester": 1
},
{
"courseId": "COSC2110",
"semester": 1
},
{
"courseId": "COSC2110",
"semester": 2
}
]
}