Lead image: Clean Data by Gene Stroman from the Noun Project, CC BY After you’ve collected en...
Public Lab is an open community which collaboratively develops accessible, open source, Do-It-Yourself technologies for investigating local environmental health and justice issues.
3 CURRENT | bhamster |
December 02, 2021 17:05
| 6 months ago
Lead image: Clean Data by Gene Stroman from the Noun Project, CC BY After you’ve collected environmental data from a sensor, monitor, or other piece of equipment, one of the next steps is to organize and “clean” it! Cleaning includes making sure the dataset is complete and consistent. Organizing the data into a table in a meaningful way gets it ready for making charts, graphs, and other visualizations. Below are some resources on cleaning data, including making tables of tidy data. Making tables of tidy dataImages: Illustrations from the Openscapes blog “Tidy Data for reproducibility, efficiency, and collaboration” by Julia Lowndes and Allison Horst, CC BY
An example of “tidy data” from an air quality sensor might look like this: Each variable forms a column: sensor ID number, date, time, and the air quality measurement of particulate matter are individual variables. Each variable gets its own column in the table. The column header at the top lists the variable name and its units of measurement. Each observation forms a row: this sensor took an air quality measurement every minute. Each measurement gets its own row in the table. Each cell is a single measurement: each block in the table shows one piece of data---one time, one PM measurement, etc. Cleaning dataMore to come here! Questions on organizing and cleaning dataQuestions tagged with [questions:data-cleaning] ActivitiesActivity posts tagged with [activities:data-cleaning] More resources on organizing and cleaning data
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2 | bhamster |
November 30, 2021 23:25
| 6 months ago
Lead image: Clean Data by Gene Stroman from the Noun Project, CC BY After you’ve collected environmental data from a sensor, monitor, or other piece of equipment, one of the next steps is to organize and “clean” it! Cleaning includes making sure the dataset is complete and consistent. Organizing the data into a table in a meaningful way gets it ready for making charts, graphs, and other visualizations. Below are some resources on cleaning data, including making tables of tidy data. Making tables of tidy dataImages: Illustrations from the Openscapes blog “Tidy Data for reproducibility, efficiency, and collaboration” by Julia Lowndes and Allison Horst, CC BY
An example of “tidy data” from an air quality sensor might look like this: Each variable forms a column: sensor ID number, date, time, and the air quality measurement of particulate matter are individual variables. Each variable gets its own column in the table. The column header at the top lists the variable name and its units of measurement. Each observation forms a row: this sensor took an air quality measurement every minute. Each measurement gets its own row in the table. Each cell is a single measurement: each block in the table shows one piece of data---one time, one PM measurement, etc. Cleaning dataMore to come here! Questions on organizing and cleaning dataQuestions tagged with [questions:data-cleaning] ActivitiesActivity posts tagged with [activities:data-cleaning] More resources on organizing and cleaning data
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1 | bhamster |
November 30, 2021 23:22
| 6 months ago
Lead image: Clean Data by Gene Stroman from the Noun Project, CC BY After you’ve collected environmental data from a sensor, monitor, or other piece of equipment, one of the next steps is to organize and “clean” it! Cleaning includes making sure the dataset is complete and consistent. Organizing the data into a table in a meaningful way gets it ready for making charts, graphs, and other visualizations. Below are some resources on cleaning data, including making tables of tidy data. Making tables of tidy dataImages: Illustrations from the Openscapes blog “Tidy Data for reproducibility, efficiency, and collaboration” by Julia Lowndes and Allison Horst, CC BY
An example of “tidy data” from an air quality sensor might look like this: Each variable forms a column: sensor ID number, date, time, and the air quality measurement of particulate matter are individual variables. Each variable gets its own column in the table. The column header at the top lists the variable name and its units of measurement. Each observation forms a row: this sensor took an air quality measurement every minute. Each measurement gets its own row in the table. Each cell is a single measurement: each block in the table shows one piece of data---one time, one PM measurement, etc. Cleaning dataMore to come here! Questions on organizing and cleaning dataQuestions tagged with [questions:data-cleaning] ActivitiesActivity posts tagged with [activities:data-cleaning] More resources on organizing and cleaning data
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0 | bhamster |
November 30, 2021 23:19
| 6 months ago
Lead image: Clean Data by Gene Stroman from the Noun Project, CC BY After you’ve collected environmental data from a sensor, monitor, or other piece of equipment, one of the next steps is to organize and “clean” it! Cleaning includes making sure the dataset is complete and consistent. Organizing the data into a table in a meaningful way gets it ready for making charts, graphs, and other visualizations. Below are some resources on cleaning data, including making tables of tidy data. Making tables of tidy dataImages: Illustrations from the Openscapes blog “Tidy Data for reproducibility, efficiency, and collaboration” by Julia Lowndes and Allison Horst, CC BY
An example of “tidy data” from an air quality sensor might look like this: Each variable forms a column: sensor ID number, date, time, and the air quality measurement of particulate matter are individual variables. Each variable gets its own column in the table. The column header at the top lists the variable name and its units of measurement. Each observation forms a row: this sensor took an air quality measurement every minute. Each measurement gets its own row in the table. Each cell is a single measurement: each block in the table shows one piece of data---one time, one PM measurement, etc. Cleaning dataMore to come here! Questions on organizing and cleaning dataQuestions tagged with [questions:data-cleaning] ActivitiesActivity posts tagged with [activities:data-cleaning] More resources on organizing and cleaning data
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