Creating a threshold after a certain about of consistent values The 2019 Stack Overflow Developer Survey Results Are InHow to drop rows of Pandas DataFrame whose value in certain columns is NaNDplyr or data.table consolidate consecutive rows within grouped data based on value in another columnCombining rows for selected columnsConditionally create new column in Rdplyr group by RunID carry values to next groupData Processing in RHow to mutate a column given a dataframe that has the conditions?Gathering nonempty rows (POSIXct format) from diffrent columns for the same UserID in a single rowR subset data.frame on timestampsCalculating time until first steering correction
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Creating a threshold after a certain about of consistent values
The 2019 Stack Overflow Developer Survey Results Are InHow to drop rows of Pandas DataFrame whose value in certain columns is NaNDplyr or data.table consolidate consecutive rows within grouped data based on value in another columnCombining rows for selected columnsConditionally create new column in Rdplyr group by RunID carry values to next groupData Processing in RHow to mutate a column given a dataframe that has the conditions?Gathering nonempty rows (POSIXct format) from diffrent columns for the same UserID in a single rowR subset data.frame on timestampsCalculating time until first steering correction
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I have a driving experiment where participants steer to account for heading error. Here is an example of my dataframe: 1
Currently, I have code that sets a threshold for steering wheel angle (SWA), and for each ppid and trialn, looks down the SWA column finds the first value above that threshold and then selects the corresponding row of data in order to get a timestamp for me to later calculate a response time for participants steering:
SWA_threshold = 0.1
threshold <-workingdata %>%
group_by(ppid,trialn) %>%
filter(abs(SWA) > SWA_threshold) %>%
filter(row_number() == 1) %>%
ungroup() %>%
transmute(ppid, heading, trialn, cameraoffset, SWAThres = SWA,
FirstSWATimeThres = timestamp, ThresWorld_x = World_x,
ThresWorld_z = World_z, ThresWorldYaw = WorldYaw, ThresYawRate_seconds =
YawRate_seconds, ThresYawRateChange = YawRateChange)
However, I have realised that a one off value for a threshold is not good - what I really want is code that selects a corresponding row after multiple consecutive values in the SWA column are over threshold i.e. 5, which means there is a consistent wheel turn.
Does anybody have any ideas on how I would edit my code to implement this new type of threshold?
r dataframe dplyr analysis
asked Mar 8 at 9:54
Courtney GoodridgeCourtney Goodridge
33
add a comment |
I have a driving experiment where participants steer to account for heading error. Here is an example of my dataframe: 1
Currently, I have code that sets a threshold for steering wheel angle (SWA), and for each ppid and trialn, looks down the SWA column finds the first value above that threshold and then selects the corresponding row of data in order to get a timestamp for me to later calculate a response time for participants steering:
SWA_threshold = 0.1
threshold <-workingdata %>%
group_by(ppid,trialn) %>%
filter(abs(SWA) > SWA_threshold) %>%
filter(row_number() == 1) %>%
ungroup() %>%
transmute(ppid, heading, trialn, cameraoffset, SWAThres = SWA,
FirstSWATimeThres = timestamp, ThresWorld_x = World_x,
ThresWorld_z = World_z, ThresWorldYaw = WorldYaw, ThresYawRate_seconds =
YawRate_seconds, ThresYawRateChange = YawRateChange)
However, I have realised that a one off value for a threshold is not good - what I really want is code that selects a corresponding row after multiple consecutive values in the SWA column are over threshold i.e. 5, which means there is a consistent wheel turn.
Does anybody have any ideas on how I would edit my code to implement this new type of threshold?
r dataframe dplyr analysis
asked Mar 8 at 9:54
Courtney GoodridgeCourtney Goodridge
33
add a comment |
I have a driving experiment where participants steer to account for heading error. Here is an example of my dataframe: 1
Currently, I have code that sets a threshold for steering wheel angle (SWA), and for each ppid and trialn, looks down the SWA column finds the first value above that threshold and then selects the corresponding row of data in order to get a timestamp for me to later calculate a response time for participants steering:
SWA_threshold = 0.1
threshold <-workingdata %>%
group_by(ppid,trialn) %>%
filter(abs(SWA) > SWA_threshold) %>%
filter(row_number() == 1) %>%
ungroup() %>%
transmute(ppid, heading, trialn, cameraoffset, SWAThres = SWA,
FirstSWATimeThres = timestamp, ThresWorld_x = World_x,
ThresWorld_z = World_z, ThresWorldYaw = WorldYaw, ThresYawRate_seconds =
YawRate_seconds, ThresYawRateChange = YawRateChange)
However, I have realised that a one off value for a threshold is not good - what I really want is code that selects a corresponding row after multiple consecutive values in the SWA column are over threshold i.e. 5, which means there is a consistent wheel turn.
Does anybody have any ideas on how I would edit my code to implement this new type of threshold?
r dataframe dplyr analysis
asked Mar 8 at 9:54
Courtney GoodridgeCourtney Goodridge
33
I have a driving experiment where participants steer to account for heading error. Here is an example of my dataframe: 1
Currently, I have code that sets a threshold for steering wheel angle (SWA), and for each ppid and trialn, looks down the SWA column finds the first value above that threshold and then selects the corresponding row of data in order to get a timestamp for me to later calculate a response time for participants steering:
SWA_threshold = 0.1
threshold <-workingdata %>%
group_by(ppid,trialn) %>%
filter(abs(SWA) > SWA_threshold) %>%
filter(row_number() == 1) %>%
ungroup() %>%
transmute(ppid, heading, trialn, cameraoffset, SWAThres = SWA,
FirstSWATimeThres = timestamp, ThresWorld_x = World_x,
ThresWorld_z = World_z, ThresWorldYaw = WorldYaw, ThresYawRate_seconds =
YawRate_seconds, ThresYawRateChange = YawRateChange)
However, I have realised that a one off value for a threshold is not good - what I really want is code that selects a corresponding row after multiple consecutive values in the SWA column are over threshold i.e. 5, which means there is a consistent wheel turn.
Does anybody have any ideas on how I would edit my code to implement this new type of threshold?
r dataframe dplyr analysis
r dataframe dplyr analysis
asked Mar 8 at 9:54
Courtney GoodridgeCourtney Goodridge
33
asked Mar 8 at 9:54
Courtney GoodridgeCourtney Goodridge
33
asked Mar 8 at 9:54
Courtney GoodridgeCourtney Goodridge
33
asked Mar 8 at 9:54
Courtney GoodridgeCourtney Goodridge
33
asked Mar 8 at 9:54
Courtney GoodridgeCourtney Goodridge
33
33
add a comment |
add a comment |
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