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author | Jehiah Czebotar <jehiah@gmail.com> | 2015-01-08 13:38:55 -0500 |
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committer | Jehiah Czebotar <jehiah@gmail.com> | 2015-01-08 13:38:55 -0500 |
commit | 06310ae949b92e4b355e1b418deafc07e53f9101 (patch) | |
tree | f4c4120ecb281e6a3dfad3632e02feaf89a83835 | |
parent | 45101596a07f0b59d219ec95aef1ded767dba64d (diff) | |
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update docs
-rw-r--r-- | README.markdown | 4 |
1 files changed, 2 insertions, 2 deletions
diff --git a/README.markdown b/README.markdown index d68202f..a632121 100644 --- a/README.markdown +++ b/README.markdown @@ -73,8 +73,8 @@ Generate an ascii bar chart for input data (this is like a visualization of `uni 14:40 [ 49] ∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎ 14:41 [ 14] ∎∎∎∎∎∎∎∎∎∎∎∎∎∎ -bar_chart.py also supports ingesting aggregated values. Simply provide a two column input of key<space>value: +`bar_chart.py` and `histogram.py` also support ingesting pre-aggregated values. Simply provide a two column input of `count<whitespace>value` for `-a` or `value<whitespace>count` for `-A`: - $ cat data | uniq -c | bar_chart.py --sort-keys --agg-values + $ cat data | uniq -c | bar_chart.py -a This is very convenient if you pull data out, say Hadoop or MySQL already aggregated. |