Flatten transformation for the json-string column (data flow in ADF) - azure-data-factory-2

I copy a csv file with a json-string column to the data flow.
I want to flatten it by the json-string column, but the column is not recognized as a json format.
How do I convert it to json-format column, or do you have other ways to deal with it? Thank you

You could ref my answer here: https://stackoverflow.com/a/65770042/10549281
If you have any other concerns, please feel free to let me know.
HTH.

Related

What is this data type? It's some input data from leetcode

I'm doing some exercises of Databases from LeetCode. I want to test my codes on my laptop using MySQL. I hope to have a easy way to import data.
Here is the input data from LeetCode:\
{"headers":{"insurance":["PID","TIV_2015","TIV_2016","LAT","LON"]},"rows":
{"insurance":[[1,224.17,952.73,32.4,20.2],[2,224.17,900.66,52.4,32.7],
[3,824.61,645.13,72.4,45.2],[4,424.32,323.66,12.4,7.7],
[5,424.32,282.9,12.4,7.7],[6,625.05,243.53,52.5,32.8],
[7,424.32,968.94,72.5,45.3],[8,624.46,714.13,12.5,7.8],
[9,425.49,463.85,32.5,20.3],[10,624.46,776.85,12.4,7.7],
[11,624.46,692.71,72.5,45.3],[12,225.93,933,12.5,7.8],
[13,824.61,786.86,32.6,20.3],[14,824.61,935.34,52.6,32.8]]}}
What is the data type?
This is a JSON string. JSON is a common data interchange format.

Transforming date (set by default) into value (format: double/currency)

I have a question regarding Excel and more specially the cases once you got your currency values into date. Is there an easy way to transform them using VBA?
For example I got 5.95$ for example transformed into May-95.
I want to create a macro (easier if possible) which is formatting the whole column into values in format double.
Thank you in advance and sorry if my question is dumb for some of you.
Regards,
Martin

Panda's DataFrame dump to CSV file is not decoding values correctly. It has Bytea data as columns

I have a complex table structure in the Database, which I am reading Panda's DataFrame. While printing DataFrame everything is printing correctly but when I dump in CSV or convert it to a list (each of DataFrame row as list) I see the following data at few columns:
<memory at 0x11a2c4640>
After debugging a little more I came to know they are BYTEA columns of Postgres and perhaps the conversation is falling. But actual confusion is if the print is fine, why write to CSV is not working. Is there any way to raw dump dataFrames?
Try to save the csv with an special encoding:
df.to_csv(r"C:\your path\ file.csv, index =True, encoding='utf-8-sig')
Try changing the type of the column, which holds BYTEA data
df[col_name] = df[col_name].astype(bytes)
df.to_csv(filename)

How do I convert this data into a tabular format?

This is the data: https://github.com/sealneaward/nba-movement-data/blob/master/data/01.01.2016.CHA.at.TOR.7z
I am not sure how to convert this data into a dataframe (likely multiple dataframes). Can anyone help me or direct me to a good resource?

Purpose of Json schema file while loading data into Big query from a csv file

Can someone please help me by stating the purpose of providing the json schema file while loading a file to BQtable using bq command. what are the advantages?
Dose this file help to maintain data integrity by avoiding any column swap ?
Regards,
Sreekanth
Specifying a JSON schema--instead of relying on auto-detect--means that you are ensured to get the expected types for each column being loaded. If you have data that looks like this, for example:
1,'foo',true
2,'bar',false
3,'baz',true
Schema auto-detection would infer that the type of the first column is an INTEGER (a.k.a. INT64). Maybe you plan to load more data in the future, though, that looks like this:
3.14,'foo',true
1.59,'bar',false
-2.001,'baz',true
In that case, you probably want the first column to have type FLOAT (a.k.a. FLOAT64) instead. If you provide a schema when you load the first file, you can specify a type of FLOAT for that column explicitly.