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author | Egor Tensin <Egor.Tensin@gmail.com> | 2016-06-18 06:22:54 +0300 |
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committer | Egor Tensin <Egor.Tensin@gmail.com> | 2016-06-18 06:22:54 +0300 |
commit | 5ec558eed235176be9a2e7b8ab5b56f54bc6263d (patch) | |
tree | 5f8af7b0e7de733be15d08ccf9b4aca6b4b56528 /README.md | |
parent | README update (diff) | |
download | vk-scripts-5ec558eed235176be9a2e7b8ab5b56f54bc6263d.tar.gz vk-scripts-5ec558eed235176be9a2e7b8ab5b56f54bc6263d.zip |
README update
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-rw-r--r-- | README.md | 36 |
1 files changed, 20 insertions, 16 deletions
@@ -89,22 +89,26 @@ You can change that by supplying either `date` (to group by dates) or `weekday` For example (assuming that both Jane and Joe spent their time online on Friday, June 17, 2016). - > online_duration.py --output-format json --grouping date db.csv - [ - { - "date": "2016-06-17", - "duration": "1:47:17" - } - ] - - > online_duration.py --output-format csv --grouping weekday db.csv - Monday,0:00:00 - Tuesday,0:00:00 - Wednesday,0:00:00 - Thursday,0:00:00 - Friday,1:47:17 - Saturday,0:00:00 - Sunday,0:00:00 +``` +> online_duration.py --output-format json --grouping date db.csv +[ + { + "date": "2016-06-17", + "duration": "1:47:17" + } +] +``` + +``` +> online_duration.py --output-format csv --grouping weekday db.csv +Monday,0:00:00 +Tuesday,0:00:00 +Wednesday,0:00:00 +Thursday,0:00:00 +Friday,1:47:17 +Saturday,0:00:00 +Sunday,0:00:00 +``` In my opinion, the script's most useful feature is the ability to easily create plots that represent the text data (like in the examples above). |