> ## Documentation Index
> Fetch the complete documentation index at: https://axionquant.com/llms.txt?v=2
> Use this file to discover all available pages before exploring further.

# Profiles

> Access company profiles, key statistics, analyst recommendations, market summaries, and earnings calendars.

The `client.profiles` namespace aggregates company-level descriptive and analytical data, from business summaries to dividend calendars.

## Methods

### `profile`

Returns the asset profile including a business summary and sector/industry classification.

<ParamField path="ticker" type="string" required>
  The stock ticker symbol (e.g. `"AAPL"`).
</ParamField>

```python theme={null}
profile = client.profiles.profile("AAPL")
print(profile["longBusinessSummary"])
print(profile["sector"])    # Technology
print(profile["industry"])  # Consumer Electronics
```

***

### `info`

Returns structured company information including address, employee count, website, and executives.

<ParamField path="ticker" type="string" required>
  The stock ticker symbol.
</ParamField>

```python theme={null}
info = client.profiles.info("MSFT")
print(info["website"])       # https://www.microsoft.com
print(info["fullTimeEmployees"])
```

***

### `statistics`

Returns key financial ratios and valuation statistics such as P/E, P/B, EPS, beta, and market cap.

<ParamField path="ticker" type="string" required>
  The stock ticker symbol.
</ParamField>

```python theme={null}
stats = client.profiles.statistics("GOOGL")
print(stats["trailingPE"])
print(stats["priceToBook"])
print(stats["beta"])
```

***

### `summary`

Returns a market data summary including current price, volume, 52-week range, and average volume.

<ParamField path="ticker" type="string" required>
  The stock ticker symbol.
</ParamField>

```python theme={null}
summary = client.profiles.summary("TSLA")
print(summary["regularMarketPrice"])
print(summary["fiftyTwoWeekHigh"])
print(summary["averageVolume"])
```

***

### `recommendation`

Returns analyst recommendation trends, showing buy/hold/sell counts over recent periods.

<ParamField path="ticker" type="string" required>
  The stock ticker symbol.
</ParamField>

```python theme={null}
recs = client.profiles.recommendation("AMZN")
for period in recs:
    print(period["period"], period["strongBuy"], period["buy"], period["hold"], period["sell"])
```

***

### `calendar`

Returns upcoming earnings dates and dividend information for the ticker.

<ParamField path="ticker" type="string" required>
  The stock ticker symbol.
</ParamField>

```python theme={null}
calendar = client.profiles.calendar("AAPL")
print(calendar["earnings"]["earningsDate"])
print(calendar["dividendDate"])
print(calendar["exDividendDate"])
```

<Note>
  The `calendar` method returns forward-looking dates. If no upcoming earnings date is scheduled, the field may be absent.
</Note>

## Example: Full workflow

```python theme={null}
from axion import Axion

client = Axion(api_key="your_api_key_here")

ticker = "NVDA"

# Business description
profile = client.profiles.profile(ticker)
print(profile["longBusinessSummary"][:200])

# Company contact info
info = client.profiles.info(ticker)
print(info["website"], info["city"], info["country"])

# Valuation metrics
stats = client.profiles.statistics(ticker)
print(f"P/E: {stats['trailingPE']}, Beta: {stats['beta']}")

# Live market summary
summary = client.profiles.summary(ticker)
print(f"Price: {summary['regularMarketPrice']}")

# Analyst consensus
recs = client.profiles.recommendation(ticker)
print(recs[0])

# Next earnings date
cal = client.profiles.calendar(ticker)
print(cal["earnings"]["earningsDate"])
```