data-matrix 0.2.0

Labeled numeric matrices with file ingest (CSV/TSV/etc.), symmetric fill, and fast label-based lookup.
Documentation
city name1,city name2,distance,i,j
Tokyo,Seoul,1149.36,0,1
Tokyo,Beijing,2089.39,0,2
Tokyo,Bangkok,4598.95,0,3
Tokyo,Singapore,5311.22,0,4
Tokyo,Paris,9711.72,0,5
Tokyo,Madrid,10761.73,0,6
Tokyo,Rome,9852.38,0,7
Tokyo,Berlin,8915.53,0,8
Tokyo,Warsaw,8577.74,0,9
Tokyo,Los Angeles,8819.39,0,10
Tokyo,Miami,12003.89,0,11
Tokyo,Chicago,10141.41,0,12
Tokyo,New York City,10851.73,0,13
Tokyo,Toronto,10351.69,0,14
Seoul,Beijing,952.33,1,2
Seoul,Bangkok,3722.1,1,3
Seoul,Singapore,4671.94,1,4
Seoul,Paris,8965.73,1,5
Seoul,Madrid,9995.44,1,6
Seoul,Rome,8966.28,1,7
Seoul,Berlin,8126.78,1,8
Seoul,Warsaw,7740.37,1,9
Seoul,Los Angeles,9585.8,1,10
Seoul,Miami,12422.96,1,11
Seoul,Chicago,10509.84,1,12
Seoul,New York City,11052.58,1,13
Seoul,Toronto,10601.16,1,14
Beijing,Bangkok,3296.04,2,3
Beijing,Singapore,4471.89,2,4
Beijing,Paris,8216.99,2,5
Beijing,Madrid,9222.48,2,6
Beijing,Rome,8125.19,2,7
Beijing,Berlin,7357.55,2,8
Beijing,Warsaw,6941.31,2,9
Beijing,Los Angeles,10061.74,2,10
Beijing,Miami,12513.44,2,11
Beijing,Chicago,10603.49,2,12
Beijing,New York City,10989.09,2,13
Beijing,Toronto,10590.0,2,14
Bangkok,Singapore,1426.76,3,4
Bangkok,Paris,9443.1,3,5
Bangkok,Madrid,10181.53,3,6
Bangkok,Rome,8828.72,3,7
Bangkok,Berlin,8603.25,3,8
Bangkok,Warsaw,8089.76,3,9
Bangkok,Los Angeles,13303.07,3,10
Bangkok,Miami,15620.24,3,11
Bangkok,Chicago,13772.87,3,12
Bangkok,New York City,13931.98,3,13
Bangkok,Toronto,13631.66,3,14
Singapore,Paris,10729.02,4,5
Singapore,Madrid,11380.77,4,6
Singapore,Rome,10016.63,4,7
Singapore,Berlin,9916.3,4,8
Singapore,Warsaw,9399.36,4,9
Singapore,Los Angeles,14120.98,4,10
Singapore,Miami,16969.48,4,11
Singapore,Chicago,15071.86,4,12
Singapore,New York City,15332.5,4,13
Singapore,Toronto,15000.78,4,14
Paris,Madrid,1052.89,5,6
Paris,Rome,1105.28,5,7
Paris,Berlin,877.46,5,8
Paris,Warsaw,1366.55,5,9
Paris,Los Angeles,9085.51,5,10
Paris,Miami,7356.57,5,11
Paris,Chicago,6650.63,5,12
Paris,New York City,5837.24,5,13
Paris,Toronto,6000.94,5,14
Madrid,Rome,1364.17,6,7
Madrid,Berlin,1869.15,6,8
Madrid,Warsaw,2289.85,6,9
Madrid,Los Angeles,9362.65,6,10
Madrid,Miami,7090.75,6,11
Madrid,Chicago,6724.66,6,12
Madrid,New York City,5768.0,6,13
Madrid,Toronto,6036.01,6,14
Rome,Berlin,1182.55,7,8
Rome,Warsaw,1314.97,7,9
Rome,Los Angeles,10188.99,7,10
Rome,Miami,8339.5,7,11
Rome,Chicago,7740.32,7,12
Rome,New York City,6889.94,7,13
Rome,Toronto,7081.23,7,14
Berlin,Warsaw,517.17,8,9
Berlin,Los Angeles,9309.68,8,10
Berlin,Miami,7995.91,8,11
Berlin,Chicago,7083.44,8,12
Berlin,New York City,6385.0,8,13
Berlin,Toronto,6476.09,8,14
Warsaw,Los Angeles,9636.88,9,10
Warsaw,Miami,8487.17,9,11
Warsaw,Chicago,7511.05,9,12
Warsaw,New York City,6854.2,9,13
Warsaw,Toronto,6921.53,9,14
Los Angeles,Miami,3758.77,10,11
Los Angeles,Chicago,2803.97,10,12
Los Angeles,New York City,3935.75,10,13
Los Angeles,Toronto,3494.31,10,14
Miami,Chicago,1917.31,11,12
Miami,New York City,1757.96,11,13
Miami,Toronto,1990.55,11,14
Chicago,New York City,1144.29,12,13
Chicago,Toronto,701.07,12,14
New York City,Toronto,550.36,13,14