leiap.time¶
This file contains functions related to survey search time calculations
Functions
clean_datetimes(df[, dt_col]) |
Filter datetimes and correct for timezone issues |
correct_timezone(df[, dt_col]) |
Account for some timezone issues |
calc_search_time(df[, dt_col, warn]) |
Calculate search times in seconds |
filter_times(df[, t_col, t_lim, dist_col, …]) |
Put time and distance restrictions on the time data. |
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leiap.time.clean_datetimes(df, dt_col='DataDate')[source]¶ Filter datetimes and correct for timezone issues
Parameters: - df (pandas DataFrame) – DataFrame of point observations
- dt_col (str) – Column name for datetime data
Returns: df – Identical to input DataFrame with an added ‘dt_adj’ column representing datetimes filtered and correct (see Notes)
Return type: pandas DataFrame
Notes
1. Points collected in 2014 did not have their times recorded (only dates); they are assigned a time of 00:00:00 by the database. In the new dt_adj column, they are assigned NaT type. If you want to access just the dates, you can do so with the original dt_col (DataDate by default). 2. When points are downloaded from handheld GPS devices, their times are converted to the timezone of the laptop on which they are downloaded. Before we realized this, a lot of points were uploaded on machines set to U.S. Pacific Time. As a result, some times need to be adjusted by 9 hours.
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leiap.time.correct_timezone(df, dt_col='DataDate')[source]¶ Account for some timezone issues
Parameters: - df (pandas DataFrame) – DataFrame of point observations
- dt_col (str) – Column name for datetime data
Returns: df – Identical to input DataFrame with datetimes fixed so that they all range from 06:30:00-21:30:00. In reality, the latest times are approx 15:00:00
Return type: pandas DataFrame
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leiap.time.calc_search_time(df, dt_col='dt_adj', warn='enable')[source]¶ Calculate search times in seconds
Parameters: - df (pandas DataFrame of points) – Must have columns ‘FieldNumber’, ‘SurveyorName’, ‘SurveyPointId’
- dt_col (str) – Column name for datetime data
- warn ({'enable', 'disable'}) – Specify whether or not you want the generic warning message.
Returns: df – Identical to input DataFrame with added ‘search_time’ and ‘dist’ columns representing search time in seconds, and distance from previous point in meters
Return type: pandas DataFrame
Notes
This is a naive calculation that doesn’t discard any times. You will want to filter values further before using in any interpretively meaningful way.