> ## Documentation Index
> Fetch the complete documentation index at: https://mintlify.com/theOehrly/Fast-F1/llms.txt
> Use this file to discover all available pages before exploring further.
# Results API
> Reference for FastF1 SessionResults and DriverResult classes
The SessionResults and DriverResult classes provide access to driver information and session results.
## SessionResults
DataFrame containing session results and driver information for all drivers in a session.
**Constructor:**
SessionResults objects are typically accessed through the `Session.results` property rather than instantiated directly.
***
## Available Columns
### Driver Information
* `DriverNumber` (str): Driver's racing number as string
* `BroadcastName` (str): Name as shown in broadcasts
* `Abbreviation` (str): Three-letter driver abbreviation (e.g., 'VER', 'HAM', 'LEC')
* `FullName` (str): Driver's full name (e.g., 'Max Verstappen')
* `FirstName` (str): Driver's first name
* `LastName` (str): Driver's last name
* `HeadshotUrl` (str): URL to driver's headshot image
* `CountryCode` (str): Driver's country code (e.g., 'NLD', 'GBR')
### Team Information
* `TeamName` (str): Team name (short version without title sponsors)
* `TeamColor` (str): Hex color code associated with the team (e.g., '3671C6' for Red Bull)
### API Identifiers
* `DriverId` (str): Driver identifier used by Ergast API
* `TeamId` (str): Constructor identifier used by Ergast API
### Result Information
#### All Sessions
* `Position` (float64): Driver's finishing position
* Available for: Race, Qualifying, Sprint, Sprint Shootout, Sprint Qualifying
* Accounts for post-race penalties and disqualifications in Race/Qualifying/Sprint sessions
* Uses NaN for DNS (Did Not Start)
#### Race/Sprint Sessions
* `ClassifiedPosition` (str): Official classification result
* Integer value if officially classified
* 'R' (Retired), 'D' (Disqualified), 'E' (Excluded), 'W' (Withdrawn), 'F' (Failed to qualify), 'N' (Not classified)
* `GridPosition` (float64): Starting grid position
* `Status` (str): Finish status or DNF reason
* Examples: 'Finished', '+ 1 Lap', 'Crash', 'Gearbox', 'Engine'
* `Time` (timedelta64\[ns]): Total race time
* Only available if driver was not more than one lap behind the leader
* `Points` (float64): Championship points earned
* `Laps` (float64): Number of laps completed
#### Qualifying Sessions
* `Q1` (timedelta64\[ns]): Best Q1 lap time
* `Q2` (timedelta64\[ns]): Best Q2 lap time
* `Q3` (timedelta64\[ns]): Best Q3 lap time
SessionResults is indexed by driver number and sorted by finishing position by default.
***
## Usage with Session
**Accessing Results:**
```python theme={null}
import fastf1
# Load session
session = fastf1.get_session(2023, 'Monaco', 'Race')
session.load()
# Get session results
results = session.results
# View all results
print(results[['Position', 'Abbreviation', 'TeamName', 'Points']])
```
**Output:**
```
Position Abbreviation TeamName Points
1 1.0 VER Red Bull Racing 25.0
11 2.0 PER Red Bull Racing 18.0
16 3.0 LEC Ferrari 15.0
...
```
***
## Filtering and Querying
```python theme={null}
# Get specific driver by index (driver number)
ver_result = results.loc['1']
print(ver_result['FullName']) # 'Max Verstappen'
# Filter by team
ferrari = results[results['TeamName'] == 'Ferrari']
print(ferrari[['Abbreviation', 'Position']])
# Get top 3
top_3 = results.head(3)
print(top_3[['Position', 'Abbreviation', 'Time']])
# Get drivers who finished
finished = results[results['Status'] == 'Finished']
# Get drivers who DNF'd
dnf = results[results['Status'] != 'Finished']
print(dnf[['Abbreviation', 'Status']])
```
***
## Qualifying Results
```python theme={null}
# Load qualifying session
quali = fastf1.get_session(2023, 'Monaco', 'Q')
quali.load()
results = quali.results
# View qualifying times
print(results[['Position', 'Abbreviation', 'Q1', 'Q2', 'Q3']])
```
**Output:**
```
Position Abbreviation Q1 Q2 Q3
1 1.0 VER 0 days 00:01:11 0 days 00:01:10 0 days 00:01:10
16 2.0 LEC 0 days 00:01:11 0 days 00:01:10 0 days 00:01:10
...
```
***
## DriverResult
Series containing result information for a single driver.
**Accessing DriverResult:**
DriverResult objects are obtained by:
1. Using `Session.get_driver(identifier)`
2. Slicing SessionResults to a single row
```python theme={null}
# Method 1: Using get_driver()
ver = session.get_driver('VER')
print(ver['FullName']) # 'Max Verstappen'
print(ver['Position']) # 1.0
# Method 2: Slicing SessionResults
ver = session.results.loc['1'] # By driver number
print(type(ver)) #
```
***
## DriverResult Properties
All columns from SessionResults are accessible as properties:
```python theme={null}
driver = session.get_driver('VER')
# Access driver info
print(f"Name: {driver['FullName']}")
print(f"Number: {driver['DriverNumber']}")
print(f"Team: {driver['TeamName']}")
print(f"Country: {driver['CountryCode']}")
# Access result info
print(f"Position: {driver['Position']}")
print(f"Points: {driver['Points']}")
print(f"Status: {driver['Status']}")
```
***
### dnf Property
Check if a driver did not finish.
True if driver did not finish (DNF)
```python theme={null}
driver = session.get_driver('VER')
if driver.dnf:
print(f"{driver['Abbreviation']} did not finish: {driver['Status']}")
else:
print(f"{driver['Abbreviation']} finished in position {driver['Position']}")
```
***
## Complete Usage Example
```python theme={null}
import fastf1
import pandas as pd
# Load race session
session = fastf1.get_session(2023, 'Monaco', 'Race')
session.load()
results = session.results
# Display results table
print("\n=== Race Results ===")
print(results[['Position', 'Abbreviation', 'TeamName', 'Status', 'Points']].to_string())
# Analyze results
print(f"\nTotal drivers: {len(results)}")
print(f"Finishers: {len(results[results['Status'] == 'Finished'])}")
print(f"DNFs: {len(results[results['Status'] != 'Finished'])}")
# Get winner details
winner = results.iloc[0]
print(f"\n=== Race Winner ===")
print(f"Driver: {winner['FullName']}")
print(f"Team: {winner['TeamName']}")
print(f"Time: {winner['Time']}")
print(f"Points: {winner['Points']}")
# Team comparison
print("\n=== Team Points ===")
team_points = results.groupby('TeamName')['Points'].sum().sort_values(ascending=False)
print(team_points)
# Get specific driver
ver = session.get_driver('VER')
print(f"\n=== {ver['FullName']} ===")
print(f"Position: {ver['Position']}")
print(f"Grid: {ver['GridPosition']}")
print(f"Points: {ver['Points']}")
print(f"DNF: {ver.dnf}")
# Compare teammates
print("\n=== Red Bull Racing ===")
rbr = results[results['TeamName'] == 'Red Bull Racing']
for _, driver in rbr.iterrows():
print(f"{driver['Abbreviation']}: P{driver['Position']:.0f} - {driver['Points']} pts")
# Qualifying comparison
quali = fastf1.get_session(2023, 'Monaco', 'Q')
quali.load()
print("\n=== Qualifying Results ===")
quali_results = quali.results
top_10 = quali_results.head(10)
for _, driver in top_10.iterrows():
q3_time = driver['Q3']
if pd.notna(q3_time):
print(f"P{driver['Position']:.0f} {driver['Abbreviation']}: {q3_time}")
```