There dataframe below has columns with mixed types. Column of interest for expansion is “Info”. Each row value in this column is a JSON object. I would like to have the headers expanded i.e. have “Info.id”,”info.x_y_cord”,”info.neutral” etc as individual columns with corresponding values under them across the dataset. I’ve tried normalizing them via pd.json_normalize(df[“Info”]) iteration but nothing seems to change.
Tag: json
Unicode decode mismatch on emojis when using json loads
I have a list of utf-8 encoded objects such as : and decode it as follows: I notice that some emojis are not converted as expected as shown below: However, when I decode an individual string, I get the expected output: I’m not sure why the first approach using json.loads gives an unexpected output. Can someone provide any pointers? Answer
Using Environment Variables as Credentials on Heroku
I need to make the “google-credentials.json” file works on heroku it’s working locally by putting the local path on my laptop but in heroku I don’t know how to do it. I search a lot, I found this solutions How to use Google API credentials json on Heroku? but I couldn’t make it works maybe the solution is old or
Accessing Json object values with the Help of a dictionary
I’ve a huge json file which has a lot of nested key value pairs. So I thought I should save the keys as dictionary values and use that dictionary values as keys to access the values from the json file. Say for example: so I thought to access the key morning value, instead of writing I should keep a dictionary
python convert single json column to multiple columns
I have a data frame with one json column and I want to split them into multiple columns. Here is a df I’ve got. I want the output as below: I’ve tried Both didn’t work. can someone please tell me how to get output that I want? Answer One way using pandas.DataFrame.explode: Output:
Running Python commands for each JSON array
I am working on some API automation scripting that will import variables from the CLI (this is used for Ansible integration) and another option to import the variables from a JSON file, if that file exists. If this file exists, the CLI is completely ignored. Currently, I have my variables set up in a file named parameters.py: I have multiple
PySpark create a json string by combining columns
I have a dataframe. I would like to perform a transformation that combines a set of columns and stuff into a json string. The columns to be combined is known ahead of time. The output should look like something below. Is there any sugggested method to achieve this? Appreciate any help on this. Answer You can create a struct type
Representing boolean with enum options in json to generate json schema with genson
I am trying to use genson python library to build a json schema which then will be used on frontend to generate a dynamic form. In this case I want frontend to create a radio button based on schema values. But I have issue with boolean types. For example, this is how my json data looks like and this is
How do I filter a Django Model by month or year from a JSON dict?
I am trying to parse through a JSON database and filter by month or by year using Django and this is driving me up a wall since this should be simple. An example of the dict key value pair in the JSON object is formatted as so: From my views.py file, I set up this function to filter the model:
API FedEX “INVALID.INPUT.EXCEPTION”,”message”:”Invalid field value in the input”
I’m trying to validade an address in FedEX API using Python 3.8 and it returns an error of invalid field value First I connect to the Auth API And it returns a message with the Auth token correctly Then I just get the token to use it in next transactions Then I prepare the next payload for address validation API