Skip to main content

Query dataframes, find issue with your notebook snippets as if a professional data scientist was pair coding with you

Project description

date-a-scientist Logo

date-a-scientist

Query dataframes, find issue with your notebook snippets as if a professional data scientist was pair coding with you.

Currently just a thin wrapper around an amazing library called pandas-ai by sinaptik-ai!

How to use it?

from date_a_scientist import DateAScientist
import pandas as pd

df = pd.DataFrame(
    [
        {"name": "Alice", "age": 25, "city": "New York"},
        {"name": "Bob", "age": 30, "city": "Los Angeles"},
        {"name": "Charlie", "age": 35, "city": "Chicago"},
    ]
)
ds = DateAScientist(
    df=df,
    llm_openai_api_token=...,  # your OpenAI API token goes here
    llm_model_name="gpt-3.5-turbo",  # by default, it uses "gpt-4o"
)

# should return "Alice"
ds.chat("What is the name of the first person?")

Additionally we can pass a description of fields, so that more meaningful questions can be asked:

ds = DateAScientist(
    df=df,
    llm_openai_api_token=...,  # your OpenAI API token goes here
    llm_model_name="gpt-3.5-turbo",  # by default, it uses "gpt-4o"
    column_descriptions={
        "name": "The name of the person",
        "age": "The age of the person",
        "city": "The city where the person lives",
    },
)

ds = DateAScientist(
    df=df,
    llm_openai_api_token=...,  # your OpenAI API token goes here
    llm_model_name="gpt-3.5-turbo",  # by default, it uses "gpt-4o"
)

# should return DataFrame with Chicago rows
ds.chat("Who lives in Chicago?")

Inspirations

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

date_a_scientist-0.1.14.tar.gz (6.0 kB view details)

Uploaded Source

Built Distribution

date_a_scientist-0.1.14-py3-none-any.whl (6.5 kB view details)

Uploaded Python 3

File details

Details for the file date_a_scientist-0.1.14.tar.gz.

File metadata

  • Download URL: date_a_scientist-0.1.14.tar.gz
  • Upload date:
  • Size: 6.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.3 CPython/3.11.3 Darwin/24.0.0

File hashes

Hashes for date_a_scientist-0.1.14.tar.gz
Algorithm Hash digest
SHA256 fd79ca4ddbfb38ef9c88df7a408d5a291bb8bb8c8219166a4012101cf4d9e8c5
MD5 9ce5a0e2c2827e8ff703d41d934cdbec
BLAKE2b-256 9d5776991edfa65ce9dd2e44c086c0af95e332772a21d0f4e553a3ec0bd7a64d

See more details on using hashes here.

File details

Details for the file date_a_scientist-0.1.14-py3-none-any.whl.

File metadata

  • Download URL: date_a_scientist-0.1.14-py3-none-any.whl
  • Upload date:
  • Size: 6.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.3 CPython/3.11.3 Darwin/24.0.0

File hashes

Hashes for date_a_scientist-0.1.14-py3-none-any.whl
Algorithm Hash digest
SHA256 f0a0213c0f9f0e9d112df3bbff0d71db7d3a5931b112d38190c6af5d62806d75
MD5 b2b48f4b00fc6adddc63528e29baae78
BLAKE2b-256 7753711f801fd9a20167724ba3194a5d9417e72d3256788e9e1b2e23de937db0

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page