Row 65619

Row ID: 65619 | Dataset Entry | Axioma AXP Content Repository

Content Data

This page contains data entry 65619 from the Axioma AXP content repository. The structured data below represents the complete record for this entry.

Well I guess the key difference is whether you're querying from a SQL dB or using a Pandas dataframe. SQL can handle billions of rows of data easily, while pandas is very slow as it scales. However, for more sophisticated modelling you would need to use Pandas. So depends on which phase of the problem you are currently. Often this is how the workflow is you look at raw data in SQL build some hypotheses around your problem and when needing to build some advance analytics pipeline do you use some predictive modelling. Pandas is often use to load data as an intermediary when building a model.

FieldValue
text Well I guess the key difference is whether you're querying from a SQL dB or using a Pandas dataframe. SQL can handle billions of rows of data easily, while pandas is very slow as it scales. However, for more sophisticated modelling you would need to use Pandas. So depends on which phase of the problem you are currently. Often this is how the workflow is you look at raw data in SQL build some hypotheses around your problem and when needing to build some advance analytics pipeline do you use some …
label r/datascience
dataType comment
communityName r/datascience
datetime 2024-05-23
username_encoded Z0FBQUFBQm5Lak1jbHl0enJ5NURMdUZTbWpzeXJtMDVZZGgtRmk5d1BSR2pQYjN3a3QtYlp3U0hCZ0dOV01wSDA4ZF92Q2JZLTJ1bDJfRVEzRVBJempldGk4ZGlKZmNwcGc9PQ==
url_encoded Z0FBQUFBQm5Lak9zaWF3aFVXSkloU2ZUMGVjUzNSYmFkVG9ZZktQZDVtWnFEeUV2Y09lR2RXemstQU45b1lLV1ZTQVl1YUdidkxFZjJxeFIzaWJuMHdwc1k2RHNaVkN0cnNBUjNQc1V2NmVjN3RvcC1qbUluM2lYZHg3ZDBaMF9qWDRWVk9UazJROXc2V3dyQU1jUnhzcl9zUHJadnBiMVBXVnFJYVhKZGlkcm95bm9JZldjQVdFdHQ5eG5tYXdIMy1fcXZGeHVENUY0VlpkMmRRUjRTbnpjOF93N3pyWTlrUT09

Raw Record

{
  "text": "Well I guess the key difference is whether you're querying from a SQL dB or using a Pandas dataframe. SQL can handle billions of rows of data easily, while pandas is very slow as it scales. However, for more sophisticated modelling you would need to use Pandas. So depends on which phase of the problem you are currently. Often this is how the workflow is you look at raw data in SQL build some hypotheses around your problem and when needing to build some advance analytics pipeline do you use some predictive modelling. Pandas is often use to load data as an intermediary when building a model.",
  "label": "r/datascience",
  "dataType": "comment",
  "communityName": "r/datascience",
  "datetime": "2024-05-23",
  "username_encoded": "Z0FBQUFBQm5Lak1jbHl0enJ5NURMdUZTbWpzeXJtMDVZZGgtRmk5d1BSR2pQYjN3a3QtYlp3U0hCZ0dOV01wSDA4ZF92Q2JZLTJ1bDJfRVEzRVBJempldGk4ZGlKZmNwcGc9PQ==",
  "url_encoded": "Z0FBQUFBQm5Lak9zaWF3aFVXSkloU2ZUMGVjUzNSYmFkVG9ZZktQZDVtWnFEeUV2Y09lR2RXemstQU45b1lLV1ZTQVl1YUdidkxFZjJxeFIzaWJuMHdwc1k2RHNaVkN0cnNBUjNQc1V2NmVjN3RvcC1qbUluM2lYZHg3ZDBaMF9qWDRWVk9UazJROXc2V3dyQU1jUnhzcl9zUHJadnBiMVBXVnFJYVhKZGlkcm95bm9JZldjQVdFdHQ5eG5tYXdIMy1fcXZGeHVENUY0VlpkMmRRUjRTbnpjOF93N3pyWTlrUT09"
}
Explore Dataset Explore Row

Entry Information