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Things on this page are fragmentary and immature notes/thoughts of the author. Please read with your own judgement!

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Comments

  1. Tablesaw’s usability is still far away from Python pandas or Spark DataFrame (even though it is the best implementation for JVM currently). I suggest you stick to Spark DataFrame or Python pandas at this time.

  2. You can display Tablesaw tables with BeakerX table display widget by running the following command.

     tech.tablesaw.beakerx.TablesawDisplayer.register()

Column

Column: nc
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3.0
Double column: nc * 4.0
Column: nc * 4.0
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Selection of size: 2
Selection of size: 2
Column: nc
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Double column: nc
Column: nc
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error: unresolved reference: Selection
col.where(Selection.with(0, 2))
          ^

Table/DataFrame

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[year, month, day, dep_time, dep_delay, arr_time, arr_delay, cancelled, carrier, tailnum, flight, origin, dest, air_time, distance, hour, min]
39 rows X 17 cols
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Table summary for: flights14.csv Column: year Measure | Value | ---------------------- n | 39 | sum | 78546 | Mean | 2014 | Min | 2014 | Max | 2014 | Range | 0 | Variance | 0 | Std. Dev | 0 | Column: month Measure | Value | ---------------------- n | 39 | sum | 39 | Mean | 1 | Min | 1 | Max | 1 | Range | 0 | Variance | 0 | Std. Dev | 0 | Column: day Measure | Value | ---------------------- n | 39 | sum | 39 | Mean | 1 | Min | 1 | Max | 1 | Range | 0 | Variance | 0 | Std. Dev | 0 | Column: dep_time Measure | Value | ----------------------------------- n | 39 | sum | 54119 | Mean | 1387.6666666666665 | Min | 553 | Max | 2133 | Range | 1580 | Variance | 197312.91228070174 | Std. Dev | 444.1991808645101 | Column: dep_delay Measure | Value | ----------------------------------- n | 39 | sum | 609 | Mean | 15.615384615384615 | Min | -10 | Max | 191 | Range | 201 | Variance | 1612.7165991902837 | Std. Dev | 40.158642895275776 | Column: arr_time Measure | Value | ---------------------------------- n | 39 | sum | 62670 | Mean | 1606.923076923077 | Min | 37 | Max | 2342 | Range | 2305 | Variance | 276612.8623481781 | Std. Dev | 525.9399797963434 | Column: arr_delay Measure | Value | ----------------------------------- n | 39 | sum | 671 | Mean | 17.2051282051282 | Min | -27 | Max | 185 | Range | 212 | Variance | 2045.4831309041833 | Std. Dev | 45.22701770959681 | Column: cancelled Measure | Value | ---------------------- n | 39 | sum | 0 | Mean | 0 | Min | 0 | Max | 0 | Range | 0 | Variance | 0 | Std. Dev | 0 | Column: carrier Category | Count | ---------------------- AA | 39 | Column: tailnum Category | Count | ---------------------- N3KDAA | 1 | N3KRAA | 1 | N3BSAA | 1 | N3HFAA | 1 | N3BJAA | 1 | N5FJAA | 1 | N328AA | 1 | N3ESAA | 1 | N5CEAA | 1 | N3JWAA | 1 | ... | ... | N336AA | 1 | N3BCAA | 1 | N3JMAA | 1 | N3CWAA | 1 | N323AA | 1 | N3EHAA | 1 | N319AA | 1 | N338AA | 1 | N327AA | 1 | N335AA | 1 | Column: flight Measure | Value | ---------------------------------- n | 39 | sum | 13176 | Mean | 337.8461538461538 | Min | 1 | Max | 1171 | Range | 1170 | Variance | 89952.60728744938 | Std. Dev | 299.9210017445417 | Column: origin Category | Count | ---------------------- JFK | 18 | EWR | 4 | LGA | 17 | Column: dest Category | Count | ---------------------- STT | 1 | BOS | 2 | DFW | 3 | AUS | 1 | IAH | 1 | SJU | 1 | ORD | 14 | SFO | 1 | SEA | 1 | LAX | 8 | MIA | 5 | PBI | 1 | Column: air_time Measure | Value | ----------------------------------- n | 39 | sum | 8026 | Mean | 205.79487179487182 | Min | 35 | Max | 365 | Range | 330 | Variance | 9050.535762483129 | Std. Dev | 95.1343038156223 | Column: distance Measure | Value | ----------------------------------- n | 39 | sum | 52212 | Mean | 1338.7692307692312 | Min | 187 | Max | 2586 | Range | 2399 | Variance | 562719.0242914981 | Std. Dev | 750.1460019832793 | Column: hour Measure | Value | ----------------------------------- n | 39 | sum | 528 | Mean | 13.538461538461533 | Min | 5 | Max | 21 | Range | 16 | Variance | 19.991902834008094 | Std. Dev | 4.4712305726732655 | Column: min Measure | Value | ----------------------------------- n | 39 | sum | 1319 | Mean | 33.820512820512825 | Min | 2 | Max | 57 | Range | 55 | Variance | 274.04588394062074 | Std. Dev | 16.554331274340885 |
[1.0, 2.0, 3.0, 7.0, 9.44242, 11.0]
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Table1 column_0 | column_1 | column_2 | column_3 | column_4 | column_5 | column_6 | column_7 | column_8 | column_9 | --------------------------------------------------------------------------------------------------------------------------------- 0 | 10 | 20 | 30 | 40 | 50 | 60 | 70 | 80 | 90 | 1 | 11 | 21 | 31 | 41 | 51 | 61 | 71 | 81 | 91 | 2 | 12 | 22 | 32 | 42 | 52 | 62 | 72 | 82 | 92 | 3 | 13 | 23 | 33 | 43 | 53 | 63 | 73 | 83 | 93 | 4 | 14 | 24 | 34 | 44 | 54 | 64 | 74 | 84 | 94 | 5 | 15 | 25 | 35 | 45 | 55 | 65 | 75 | 85 | 95 | 6 | 16 | 26 | 36 | 46 | 56 | 66 | 76 | 86 | 96 | 7 | 17 | 27 | 37 | 47 | 57 | 67 | 77 | 87 | 97 | 8 | 18 | 28 | 38 | 48 | 58 | 68 | 78 | 88 | 98 | 9 | 19 | 29 | 39 | 49 | 59 | 69 | 79 | 89 | 99 |