快速入门

# Using poetry (recommended)
poetry add "pandasai>=3.0.0b2"

# Alternative: using pip
pip install "pandasai>=3.0.0b2"

import pandasai as pai

# Get your API key from https://app.pandabi.ai
pai.api_key.set("YOUR_PANDABI_API_KEY")

import pandasai as pai

# Load your data
df = pai.read_csv("data/companies.csv")

response = df.chat("What is the average revenue by region?")
print(response)

import pandasai as pai

# Load your data
df = pai.read_csv("data/companies.csv")

# Create the data layer
companies = pai.create(
  path="my-org/companies",
  df=df,
  description="Customer companies dataset"
)

# Define a companies dataset with explicit schema
companies = pai.create(
  path="my-org/companies",
  df=df,
  description="Customer companies dataset",
  columns=[
    {
      "name": "company_name",
      "type": "string",
      "description": "The name of the company"
    },
    {
      "name": "revenue",
      "type": "float",
      "description": "The revenue of the company"
    },
    {
      "name": "region",
      "type": "string",
      "description": "The region of the company"
    }
  ]
)

# Load existing datasets
stocks = pai.load("organization/coca_cola_stock")
companies = pai.load("organization/companies")

# Query using natural language
response = stocks.chat("What is the volatility of the Coca Cola stock?")
response = companies.chat("What is the average revenue by region?")

# Query using multiple datasets 
result = pai.chat("Compare the revenue between Coca Cola and Apple", stocks, companies)

# Push datasets to the platform
stocks.push()
companies.push()