I have the attached following actions parameter part of my JSON data. 'actions': [{'action_type': 'onsite_conversion.post_save', 'value': '1'}, {'action_type': 'link_click', 'value': '2'}, {'action_type': 'post', 'value': '3'}, {'action_type': 'post_reaction', 'value': '4'}, {'action_type': 'video_view', 'value': '5'}, {'action_type': 'post_engagement', 'value': '6'}, {'action_type': 'page_engagement', 'value':…
I'm trying to find out if Pandas.read_json performs some level of autodetection. For example, I have the following data: data_records = [ { "device": "rtr1", "dc": "London", "vendor": "Cisco", }, { "device": "rtr2", "dc": "London", "vendor": "Cisco", }, { "device":…
The input is given as: rec = [b'1674278797,14.33681', b'1674278798,6.03617', b'1674278799,12.78418'] I want to get a DataFrame like: df timestamp val 0 1674278797 14.33681 1 1674278798 6.03617 2 1674278799 12.78418 What is the most efficient way? Thanks! If I can convert…
I need to pandasql library for doing some queries on my pandas dataframes. I have run the below code on a simple sample and got the following Error. Strangely, can't consider it as a query! I tried to reinstall, and…
So, I have this Function App with a Blob Trigger, however I don't need it to be polling for new blobs all the time. I'm expecting new files to be found in a container only once a day, and I…
I have my postgres installed on PC1 and I am connecting to the database using PC2. I have modified the settings so that postgres on PC1 is accessible to local network. On PC2 I am doing the following: import pandas…
I am generating a python code that automatically processes and combines JSON datasets. Meanwhile, when I access each folder, there are two JSON datasets in a folder, which are, for example download/2019/201901/dragon.csv download/2019/201901/kingdom.csv and the file names are the same…
I've been trying to convert a json response from an api to a full panadas dataframe. I tried json normalize to achieve it unfortunately i was able to split it only to one level. response = { "data": { "result":…
I have a xlsx file Country name Country code IN India SL Sri Lanka I want to convert this to a json in the format json = { {"Name":"India", "Code":"IN"}, {"Name":"Sri Lanka", "Code":"SL"} } I tried load the excel file…
I am trying to connect to azure sql database through Jupyter notebook and later to load the data into excel/csv .I have the details of server and database only .Username & password i think by default its taking my desktop…