Extracting parts of a date or time from a timestamp

When working with timestamped market data, you often need to extract specific components like the date, time, or hour. Rather than using slower row-by-row loops, you can use vectorized operations for much better performance.

String slicing with lambda functions

The primary approach uses apply() with lambda functions to extract substrings from timestamp data:

df = liberator.get_dataframe(
    liberator.query(
        name='minute_bars',
        symbols='SPY',
        as_of='2024-07-26',
        back_to='2024-07-25'
    )
)

df['Date'] = df.apply(lambda row: str(row.timestamp)[0:10], axis=1)
df['Time'] = df.apply(lambda row: str(row.timestamp)[11:16], axis=1)
df['Hour'] = df.apply(lambda row: str(row.timestamp)[11:13], axis=1)
df['DateTime'] = df.apply(lambda row: str(row.timestamp)[0:16], axis=1)
df['DateHour'] = df.apply(lambda row: str(row.timestamp)[0:13], axis=1)

df[['timestamp', 'Date', 'Time', 'Hour', 'DateTime', 'DateHour']]

This creates new columns by slicing the timestamp string at specific positions:

Column	Slice	Example Output
`Date`	`[0:10]`	`2024-07-26`
`Time`	`[11:16]`	`14:30`
`Hour`	`[11:13]`	`14`
`DateTime`	`[0:16]`	`2024-07-26 14:30`
`DateHour`	`[0:13]`	`2024-07-26 14`

Alternative: FLOOR method using Pandas DateTime

You can also use pandas built-in datetime methods:

df['seconds'] = df['timestamp'].dt.floor('s')

df['Date'] = pd.to_datetime(df["timestamp"]).dt.date

String slicing with lambda functions provides fast processing for extracting timestamp components, making it preferable to manual loops for DataFrame operations.

Python Data Science Shortcuts and Snippets

Using Market Calendar (mcal) to Identify Trading Dates

⌘I

Getting Started

What's New

Administration

CloudQuant Data Liberator Python Guide

System Monitoring

Data Science Recipes

Extracting Parts of a Date or Time from a Timestamp

Extracting parts of a date or time from a timestamp

String slicing with lambda functions

Alternative: FLOOR method using Pandas DateTime

​Extracting parts of a date or time from a timestamp

​String slicing with lambda functions

​Alternative: FLOOR method using Pandas DateTime

Extracting parts of a date or time from a timestamp

String slicing with lambda functions

Alternative: FLOOR method using Pandas DateTime