Row 4371

Row ID: 4371 | Dataset Entry | Axioma AXP Content Repository

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Hello everyone , I'm currently working on a time series forecasting project and facing a challenge with indexing my data. I'd appreciate some guidance or clarification on how to approach this.

My issue is that I cannot solely index my data by datetime; it also needs to be indexed by date and another factor, specifically the route. Here's a bit more context:

In my use case, I'm aiming to predict the number of passengers per airline route. This means that every day, there are multiple flights to multiple routes, resulting in multiple rows of data for the same date. However, using datetime alone as the index doesn't capture the uniqueness of each route's passenger count for a given day.

Could someone please advise on how I can properly index my data to address this challenge? Any suggestions or corrections to my understanding would be greatly appreciated. is the NeuralProphet cable for handling combined index(date\_route).

Thank you in advance for your assistance! Niloo

FieldValue
text Hello everyone , I'm currently working on a time series forecasting project and facing a challenge with indexing my data. I'd appreciate some guidance or clarification on how to approach this. My issue is that I cannot solely index my data by datetime; it also needs to be indexed by date and another factor, specifically the route. Here's a bit more context: In my use case, I'm aiming to predict the number of passengers per airline route. This means that every day, there are multiple flights …
label r/neuralnetworks
dataType post
communityName r/neuralnetworks
datetime 2024-04-09
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{
  "text": "Hello everyone ,  \nI'm currently working on a time series forecasting project and facing a challenge with indexing my data. I'd appreciate some guidance or clarification on how to approach this.\n\nMy issue is that I cannot solely index my data by datetime; it also needs to be indexed by date and another factor, specifically the route. Here's a bit more context:\n\nIn my use case, I'm aiming to predict the number of passengers per airline route. This means that every day, there are multiple flights to multiple routes, resulting in multiple rows of data for the same date. However, using datetime alone as the index doesn't capture the uniqueness of each route's passenger count for a given day.\n\nCould someone please advise on how I can properly index my data to address this challenge? Any suggestions or corrections to my understanding would be greatly appreciated. is the NeuralProphet cable for handling combined index(date\\_route).\n\nThank you in advance for your assistance!  \nNiloo",
  "label": "r/neuralnetworks",
  "dataType": "post",
  "communityName": "r/neuralnetworks",
  "datetime": "2024-04-09",
  "username_encoded": "Z0FBQUFBQm5LakwxbUZyUkJlZm5MV25yYW5xR0tGbWJrVDF5VVFtRTBfMGI4V2NrRU04cGlicldaWHhkTURXemN2OUNYS2JYWEh0YTkyZUp3MDNXSVh3b3N5WHFmMmlCcGc9PQ==",
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}
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