diff --git a/docs/source/index.ipynb b/docs/source/index.ipynb
index 65a59db..cd6ee99 100644
--- a/docs/source/index.ipynb
+++ b/docs/source/index.ipynb
@@ -51,7 +51,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "9240a454a1c0450eb5b5bbb8260cb74f",
+       "model_id": "aefbc5694c834e6c9d5d86696b28c512",
        "version_major": 2,
        "version_minor": 0
       },
@@ -84,7 +84,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "dc5faebcb39a46b4bab9fe1d6ac59dd1",
+       "model_id": "31566bf1ca5a4481ac29df8e2af5c069",
        "version_major": 2,
        "version_minor": 0
       },
@@ -134,12 +134,12 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "15f35d4e95474f348b8f364b5b7bdf01",
+       "model_id": "c55becb64db14d5fb42adf386a40d0ef",
        "version_major": 2,
        "version_minor": 0
       },
       "text/plain": [
-       "VBox(children=(Sheet(cells=(Cell(column_end=1, column_start=1, row_end=0, row_start=0, type='numeric', value=1…"
+       "VBox(children=(Sheet(cells=(Cell(column_end=1, column_start=1, row_end=0, row_start=0, type='float', value=1),…"
       ]
      },
      "metadata": {},
@@ -149,9 +149,9 @@
    "source": [
     "import ipywidgets as widgets\n",
     "sheet = ipysheet.sheet(rows=3, columns=2, column_headers=False, row_headers=False)\n",
-    "cell_a = ipysheet.cell(0, 1, 1, label_left='a')\n",
-    "cell_b = ipysheet.cell(1, 1, 2, label_left='b')\n",
-    "cell_sum = ipysheet.cell(2, 1, 3, label_left='sum', read_only=True)\n",
+    "cell_a = ipysheet.cell(0, 1, 1, label_left='a', type='float')\n",
+    "cell_b = ipysheet.cell(1, 1, 2, label_left='b', type='float')\n",
+    "cell_sum = ipysheet.cell(2, 1, 3, label_left='sum', type='float', read_only=True)\n",
     "\n",
     "# create a slider linked to cell a\n",
     "slider = widgets.FloatSlider(min=-10, max=10, description='a')\n",
@@ -184,7 +184,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "331eb1d230d04a2b9cf22ff0e7d34221",
+       "model_id": "b37b8eca5c8848be89723324f2d00cc9",
        "version_major": 2,
        "version_minor": 0
       },
@@ -221,12 +221,12 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "ee569f56091c4b069b0ee13367c33a60",
+       "model_id": "6ee23e4789234a5ea9649db94c533a38",
        "version_major": 2,
        "version_minor": 0
       },
       "text/plain": [
-       "VBox(children=(Sheet(cells=(Cell(column_end=1, column_start=1, row_end=0, row_start=0, type='numeric', value=1…"
+       "VBox(children=(Sheet(cells=(Cell(column_end=1, column_start=1, row_end=0, row_start=0, type='int', value=1), C…"
       ]
      },
      "metadata": {},
@@ -241,7 +241,7 @@
     "cell_sum = ipysheet.cell(2, 1, 3, label_left='sum', read_only=True)\n",
     "\n",
     "# create a slider linked to cell a\n",
-    "slider = widgets.FloatSlider(min=-10, max=10, description='a')\n",
+    "slider = widgets.IntSlider(min=-10, max=10, description='a')\n",
     "widgets.jslink((cell_a, 'value'), (slider, 'value'))\n",
     "\n",
     "@ipysheet.calculation(inputs=[cell_a, cell_b], output=cell_sum)\n",
@@ -282,7 +282,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "120d773208664b28a62edb6279d39e52",
+       "model_id": "5329d60e41b14391a3a20b8eb324d8f7",
        "version_major": 2,
        "version_minor": 0
       },
@@ -306,7 +306,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "If [flexx](http://flexx.readthedocs.io/en/stable/pyscript/index.html) is installed, Python code can be transpiled to JavaScript at runtime."
+    "Custom renderers can be JavaScript functions as well as Python functions that returns the cell style"
    ]
   },
   {
@@ -330,7 +330,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "96f01acbd7054929b95d9b6a93e80ec1",
+       "model_id": "2c8599283f5d4347895b95d24b887d47",
        "version_major": 2,
        "version_minor": 0
       },
@@ -382,76 +382,87 @@
   "widgets": {
    "application/vnd.jupyter.widget-state+json": {
     "state": {
-     "078a93ab3a954e6e9fd0cb309683ad9a": {
+     "02cee59ebef44b7cabddc13e7250526c": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "1.4.0",
+      "model_name": "IntSliderModel",
+      "state": {
+       "description": "a",
+       "layout": "IPY_MODEL_b1c054ac2a1340fb9200c5f16af5323e",
+       "max": 10,
+       "min": -10,
+       "style": "IPY_MODEL_d11ccb31354249589dd350497d7c0779",
+       "value": 1
+      }
+     },
+     "136070030dee469a91c0b5f86f8a744b": {
+      "model_module": "@jupyter-widgets/base",
+      "model_module_version": "1.1.0",
+      "model_name": "LayoutModel",
+      "state": {}
+     },
+     "1690d5f265784d0094c7492f9c9436d3": {
       "model_module": "ipysheet",
       "model_module_version": "~0.4.1",
       "model_name": "CellRangeModel",
       "state": {
        "_view_module": null,
        "_view_module_version": "",
-       "column_end": 3,
-       "column_start": 0,
-       "renderer": "negative_transpiled",
+       "type": "float",
+       "value": 2
+      }
+     },
+     "1f20ca8577d64f409dda17d6c6f0c303": {
+      "model_module": "ipysheet",
+      "model_module_version": "~0.4.1",
+      "model_name": "CellRangeModel",
+      "state": {
+       "_view_module": null,
+       "_view_module_version": "",
+       "column_end": 2,
+       "column_start": 2,
        "row_end": 2,
-       "row_start": 0,
-       "squeeze_column": false,
-       "squeeze_row": false,
-       "type": "numeric",
-       "value": [
-        [
-         -4,
-         -3,
-         -1,
-         9
-        ],
-        [
-         -1,
-         9,
-         -6,
-         9
-        ],
-        [
-         -9,
-         9,
-         -1,
-         -9
-        ]
-       ]
+       "row_start": 2,
+       "type": "float",
+       "value": 42
       }
      },
-     "120d773208664b28a62edb6279d39e52": {
+     "2911b30eab6941e7beb2ed6060e96c99": {
       "model_module": "ipysheet",
       "model_module_version": "~0.4.1",
-      "model_name": "SheetModel",
+      "model_name": "CellRangeModel",
       "state": {
-       "cells": [
-        "IPY_MODEL_1e98bbb1a81b414691f47a167cf7d12f"
-       ],
-       "layout": "IPY_MODEL_c1dbe91c4db244ceb857f8ce9401cc6a"
+       "_view_module": null,
+       "_view_module_version": "",
+       "type": "int",
+       "value": 2
       }
      },
-     "155748346e0a4bfbaa4a6cdd209755f5": {
-      "model_module": "@jupyter-widgets/base",
-      "model_module_version": "1.1.0",
-      "model_name": "LayoutModel",
+     "2c8599283f5d4347895b95d24b887d47": {
+      "model_module": "ipysheet",
+      "model_module_version": "~0.4.1",
+      "model_name": "SheetModel",
       "state": {
-       "height": "auto",
-       "width": "auto"
+       "cells": [
+        "IPY_MODEL_4855a741aca94869be3e526e3cdc5a25"
+       ],
+       "layout": "IPY_MODEL_5e79886cd1b844c28b880b373887d745"
       }
      },
-     "15f35d4e95474f348b8f364b5b7bdf01": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "1.4.0",
-      "model_name": "VBoxModel",
+     "31566bf1ca5a4481ac29df8e2af5c069": {
+      "model_module": "ipysheet",
+      "model_module_version": "~0.4.1",
+      "model_name": "SheetModel",
       "state": {
-       "children": [
-        "IPY_MODEL_9ed9cb9f61294fb0b9a97848d193c1db",
-        "IPY_MODEL_3a02c16fe28c4f269b15eea3914114b6"
+       "cells": [
+        "IPY_MODEL_ba619725ce96426ead50b7d9321b08f6",
+        "IPY_MODEL_96446474f82e4e6897772b1550e865d2",
+        "IPY_MODEL_1f20ca8577d64f409dda17d6c6f0c303"
        ],
-       "layout": "IPY_MODEL_418d6f810c4c49e18b5310d205dba504"
+       "layout": "IPY_MODEL_3bee1706c9d6466191ddc6b9eeaaec12"
       }
      },
-     "1e98bbb1a81b414691f47a167cf7d12f": {
+     "360ed33dd47241bebf26dd5366c808e5": {
       "model_module": "ipysheet",
       "model_module_version": "~0.4.1",
       "model_name": "CellRangeModel",
@@ -465,50 +476,63 @@
        "row_start": 0,
        "squeeze_column": false,
        "squeeze_row": false,
-       "type": "numeric",
+       "type": "int",
        "value": [
         [
-         10,
-         3,
-         1,
-         9
+         8,
+         0,
+         -3,
+         0
         ],
         [
-         -5,
-         7,
+         -1,
+         -7,
          -3,
          7
         ],
         [
-         1,
-         10,
-         -3,
-         1
+         -7,
+         -6,
+         8,
+         -1
         ]
        ]
       }
      },
-     "1f92a18646e94c68b9424fdbc6bff1f4": {
-      "model_module": "@jupyter-widgets/base",
-      "model_module_version": "1.1.0",
-      "model_name": "LayoutModel",
+     "3633f20c839f443d9b0ebfb984473975": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "1.4.0",
+      "model_name": "LinkModel",
       "state": {
-       "height": "auto",
-       "width": "auto"
+       "source": [
+        "IPY_MODEL_60fbd1008b794878947bf8d72afa9935",
+        "value"
+       ],
+       "target": [
+        "IPY_MODEL_e8882d237be147c190d87e8fb3564121",
+        "value"
+       ]
       }
      },
-     "260d446590784781b0ea1079242ee098": {
+     "3b08b671e1014d3f99544a4b180cbce4": {
       "model_module": "ipysheet",
       "model_module_version": "~0.4.1",
-      "model_name": "RendererModel",
+      "model_name": "CellRangeModel",
       "state": {
-       "_view_module": "ipysheet",
-       "_view_module_version": "~0.4.1",
-       "code": "\nfunction() {\n                  var the_renderer;\n                the_renderer = function flx_the_renderer (value) {\n                    return ({backgroundColor: ((value < 0))? (\"orange\") : (\"\")});\n                };\n\n  return the_renderer\n\n}()\n",
-       "name": "negative_transpiled"
+       "_view_module": null,
+       "_view_module_version": "",
+       "column_end": 0,
+       "column_start": 0,
+       "row_end": 2,
+       "row_start": 2,
+       "style": {
+        "fontWeight": "bold"
+       },
+       "type": "text",
+       "value": "sum"
       }
      },
-     "2733376ab7f14d4dbe107138963c2214": {
+     "3bee1706c9d6466191ddc6b9eeaaec12": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "1.1.0",
       "model_name": "LayoutModel",
@@ -517,63 +541,92 @@
        "width": "auto"
       }
      },
-     "2ae00660ce774f22ab24da60c086fc0e": {
+     "4855a741aca94869be3e526e3cdc5a25": {
       "model_module": "ipysheet",
       "model_module_version": "~0.4.1",
       "model_name": "CellRangeModel",
       "state": {
        "_view_module": null,
        "_view_module_version": "",
-       "read_only": true,
+       "column_end": 3,
+       "column_start": 0,
+       "renderer": "negative_transpiled",
        "row_end": 2,
-       "row_start": 2,
-       "type": "numeric",
-       "value": 3
+       "row_start": 0,
+       "squeeze_column": false,
+       "squeeze_row": false,
+       "type": "int",
+       "value": [
+        [
+         1,
+         2,
+         -4,
+         10
+        ],
+        [
+         -3,
+         5,
+         4,
+         10
+        ],
+        [
+         4,
+         8,
+         -4,
+         7
+        ]
+       ]
       }
      },
-     "2c4fa222b61a4d518c6a40c92b040f11": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "1.4.0",
-      "model_name": "FloatSliderModel",
+     "51ebae69061f4846816261b35ae62b32": {
+      "model_module": "ipysheet",
+      "model_module_version": "~0.4.1",
+      "model_name": "SheetModel",
       "state": {
-       "description": "a",
-       "layout": "IPY_MODEL_d91e09a8701e4888a34550824908ab8c",
-       "max": 10,
-       "min": -10,
-       "step": 0.1,
-       "style": "IPY_MODEL_714d355de86d4881b34fb804fe770008",
-       "value": 1
+       "cells": [
+        "IPY_MODEL_60fbd1008b794878947bf8d72afa9935",
+        "IPY_MODEL_f1ae488f0a9245938c107a68dcf959bd",
+        "IPY_MODEL_1690d5f265784d0094c7492f9c9436d3",
+        "IPY_MODEL_67a73ba0f1fd4a37a880c53e112881f2",
+        "IPY_MODEL_6123f60effa2498a86dd1c84adee9427",
+        "IPY_MODEL_3b08b671e1014d3f99544a4b180cbce4"
+       ],
+       "column_headers": false,
+       "columns": 2,
+       "layout": "IPY_MODEL_a85ee3116fdc4c698343192143b2b421",
+       "row_headers": false
       }
      },
-     "331eb1d230d04a2b9cf22ff0e7d34221": {
+     "5329d60e41b14391a3a20b8eb324d8f7": {
       "model_module": "ipysheet",
       "model_module_version": "~0.4.1",
       "model_name": "SheetModel",
       "state": {
        "cells": [
-        "IPY_MODEL_69590c5315e34d6e884458c4ed1271ec",
-        "IPY_MODEL_e93dd6c4fb4240478c3cbb535bf3d478",
-        "IPY_MODEL_a8546559d0c544af840ac5212b3fe9fd"
+        "IPY_MODEL_360ed33dd47241bebf26dd5366c808e5"
        ],
-       "layout": "IPY_MODEL_41c13784e4714966adcb8ae3d44178db",
-       "rows": 5
+       "layout": "IPY_MODEL_b3cdf33d93784df695183e0fe55efe3e"
       }
      },
-     "3a02c16fe28c4f269b15eea3914114b6": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "1.4.0",
-      "model_name": "FloatSliderModel",
+     "54da9a994bfb4769aa3d680fa70d34ac": {
+      "model_module": "ipysheet",
+      "model_module_version": "~0.4.1",
+      "model_name": "CellRangeModel",
       "state": {
-       "description": "a",
-       "layout": "IPY_MODEL_7a9609f5eb3d444485201b9424cc45eb",
-       "max": 10,
-       "min": -10,
-       "step": 0.1,
-       "style": "IPY_MODEL_3f8af119d77d4a508b090398dff5a8fd",
-       "value": 1
+       "_view_module": null,
+       "_view_module_version": "",
+       "column_end": 0,
+       "column_start": 0,
+       "row_end": 2,
+       "row_start": 2,
+       "style": {
+        "fontWeight": "bold"
+       },
+       "type": "text",
+       "value": "sum"
       }
      },
-     "3f8af119d77d4a508b090398dff5a8fd": {
+     "567b271aa9b54533a75d50c63da111f5": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "1.4.0",
       "model_name": "SliderStyleModel",
@@ -581,33 +634,28 @@
        "description_width": ""
       }
      },
-     "402e691da01e4dd2af5ef3f97e91d0a5": {
+     "5902bfe2b33b44dda27c63383745a6b8": {
       "model_module": "ipysheet",
       "model_module_version": "~0.4.1",
-      "model_name": "RendererModel",
-      "state": {
-       "_view_module": "ipysheet",
-       "_view_module_version": "~0.4.1",
-       "code": "function (value) {\n  return {\n    backgroundColor: value < 0 ?  'red' : 'green'\n  };\n}\n",
-       "name": "negative"
-      }
-     },
-     "418d6f810c4c49e18b5310d205dba504": {
-      "model_module": "@jupyter-widgets/base",
-      "model_module_version": "1.1.0",
-      "model_name": "LayoutModel",
-      "state": {}
-     },
-     "41c13784e4714966adcb8ae3d44178db": {
-      "model_module": "@jupyter-widgets/base",
-      "model_module_version": "1.1.0",
-      "model_name": "LayoutModel",
+      "model_name": "CellRangeModel",
       "state": {
-       "height": "auto",
-       "width": "auto"
+       "_view_module": null,
+       "_view_module_version": "",
+       "row_end": 4,
+       "squeeze_row": false,
+       "style": {
+        "backgroundColor": "green"
+       },
+       "type": "text",
+       "value": [
+        "a",
+        "b",
+        "c",
+        "d"
+       ]
       }
      },
-     "43172e8bacd645bca0c4289ea6de15f4": {
+     "5e79886cd1b844c28b880b373887d745": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "1.1.0",
       "model_name": "LayoutModel",
@@ -616,37 +664,20 @@
        "width": "auto"
       }
      },
-     "535bb3899bcf426389df0a9ed97c4e3d": {
+     "60fbd1008b794878947bf8d72afa9935": {
       "model_module": "ipysheet",
       "model_module_version": "~0.4.1",
       "model_name": "CellRangeModel",
       "state": {
        "_view_module": null,
        "_view_module_version": "",
-       "type": "numeric",
-       "value": 2
-      }
-     },
-     "593c55e36b1e449fba9193764c1b00ce": {
-      "model_module": "ipysheet",
-      "model_module_version": "~0.4.1",
-      "model_name": "SheetModel",
-      "state": {
-       "cells": [
-        "IPY_MODEL_b1fde7c30c954ad8b0198bc66b28a121",
-        "IPY_MODEL_aa085b146c2241c0929ced4f8d0b8cc3",
-        "IPY_MODEL_8a9a9bdb7f104943b53b06d9943c3a45",
-        "IPY_MODEL_ba0c6a1a21624d82aa23f75afdc7666c",
-        "IPY_MODEL_2ae00660ce774f22ab24da60c086fc0e",
-        "IPY_MODEL_90541fb1218742e4bcacfe67b9ee4180"
-       ],
-       "column_headers": false,
-       "columns": 2,
-       "layout": "IPY_MODEL_43172e8bacd645bca0c4289ea6de15f4",
-       "row_headers": false
+       "row_end": 0,
+       "row_start": 0,
+       "type": "float",
+       "value": 1
       }
      },
-     "6476661bcf82408dbc65f220605068dc": {
+     "6123f60effa2498a86dd1c84adee9427": {
       "model_module": "ipysheet",
       "model_module_version": "~0.4.1",
       "model_name": "CellRangeModel",
@@ -656,105 +687,70 @@
        "read_only": true,
        "row_end": 2,
        "row_start": 2,
-       "type": "numeric",
+       "type": "float",
        "value": 3
       }
      },
-     "69590c5315e34d6e884458c4ed1271ec": {
+     "67a73ba0f1fd4a37a880c53e112881f2": {
       "model_module": "ipysheet",
       "model_module_version": "~0.4.1",
       "model_name": "CellRangeModel",
       "state": {
        "_view_module": null,
        "_view_module_version": "",
-       "column_end": 3,
+       "column_end": 0,
        "column_start": 0,
-       "row_end": 0,
-       "row_start": 0,
-       "squeeze_column": false,
        "style": {
-        "backgroundColor": "red"
+        "fontWeight": "bold"
        },
-       "type": "numeric",
-       "value": [
-        0,
-        1,
-        2,
-        3
-       ]
-      }
-     },
-     "7096b52219184bbb99b0e8c2a834fcbb": {
-      "model_module": "ipysheet",
-      "model_module_version": "~0.4.1",
-      "model_name": "CellRangeModel",
-      "state": {
-       "_view_module": null,
-       "_view_module_version": "",
-       "column_end": 0,
-       "column_start": 0,
-       "row_end": 0,
-       "row_start": 0,
        "type": "text",
-       "value": "Hello"
+       "value": "b"
       }
      },
-     "714d355de86d4881b34fb804fe770008": {
+     "6ee23e4789234a5ea9649db94c533a38": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "1.4.0",
-      "model_name": "SliderStyleModel",
+      "model_name": "VBoxModel",
       "state": {
-       "description_width": ""
+       "children": [
+        "IPY_MODEL_983bf4f9d45c4e3281bb704cbf3c1491",
+        "IPY_MODEL_02cee59ebef44b7cabddc13e7250526c"
+       ],
+       "layout": "IPY_MODEL_77f6caae156442808f7121e594c518af"
       }
      },
-     "7a9609f5eb3d444485201b9424cc45eb": {
+     "77f6caae156442808f7121e594c518af": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "1.1.0",
       "model_name": "LayoutModel",
       "state": {}
      },
-     "7e19d6589d564fcca765396f70c0b799": {
+     "81a7727c6d0b456894342fa8b619a56a": {
       "model_module": "ipysheet",
       "model_module_version": "~0.4.1",
-      "model_name": "CellRangeModel",
-      "state": {
-       "_view_module": null,
-       "_view_module_version": "",
-       "column_end": 0,
-       "column_start": 0,
-       "row_end": 2,
-       "row_start": 2,
-       "type": "text",
-       "value": "World"
-      }
-     },
-     "85e2ce2478f04c629dda0e83829aab0d": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "1.4.0",
-      "model_name": "LinkModel",
+      "model_name": "RendererModel",
       "state": {
-       "source": [
-        "IPY_MODEL_f0faccde3e71426a96bf6a454802b5dd",
-        "value"
-       ],
-       "target": [
-        "IPY_MODEL_3a02c16fe28c4f269b15eea3914114b6",
-        "value"
-       ]
+       "_view_module": "ipysheet",
+       "_view_module_version": "~0.4.1",
+       "code": "function (value) {\n  return {\n    backgroundColor: value < 0 ?  'red' : 'green'\n  };\n}\n",
+       "name": "negative"
       }
      },
-     "8a9a9bdb7f104943b53b06d9943c3a45": {
+     "86e297200d5c4ab6a6576545c6bafea5": {
       "model_module": "ipysheet",
       "model_module_version": "~0.4.1",
       "model_name": "CellRangeModel",
       "state": {
        "_view_module": null,
        "_view_module_version": "",
-       "type": "numeric",
-       "value": 2
+       "read_only": true,
+       "row_end": 2,
+       "row_start": 2,
+       "type": "int",
+       "value": 3
       }
      },
-     "90541fb1218742e4bcacfe67b9ee4180": {
+     "96446474f82e4e6897772b1550e865d2": {
       "model_module": "ipysheet",
       "model_module_version": "~0.4.1",
       "model_name": "CellRangeModel",
@@ -765,72 +761,98 @@
        "column_start": 0,
        "row_end": 2,
        "row_start": 2,
-       "style": {
-        "fontWeight": "bold"
-       },
        "type": "text",
-       "value": "sum"
+       "value": "World"
       }
      },
-     "9240a454a1c0450eb5b5bbb8260cb74f": {
+     "983bf4f9d45c4e3281bb704cbf3c1491": {
       "model_module": "ipysheet",
       "model_module_version": "~0.4.1",
       "model_name": "SheetModel",
       "state": {
-       "columns": 5,
-       "layout": "IPY_MODEL_2733376ab7f14d4dbe107138963c2214",
-       "rows": 5
+       "cells": [
+        "IPY_MODEL_d46df184a60c4a67a4e6147de0d75f54",
+        "IPY_MODEL_e665dc60260d43029ff6c9f009bc71ca",
+        "IPY_MODEL_2911b30eab6941e7beb2ed6060e96c99",
+        "IPY_MODEL_bcbafc1b29b749ba809ce88c98e382e7",
+        "IPY_MODEL_86e297200d5c4ab6a6576545c6bafea5",
+        "IPY_MODEL_54da9a994bfb4769aa3d680fa70d34ac"
+       ],
+       "column_headers": false,
+       "columns": 2,
+       "layout": "IPY_MODEL_e755bf96293344d6b58f964663157da8",
+       "row_headers": false
       }
      },
-     "96f01acbd7054929b95d9b6a93e80ec1": {
+     "a85ee3116fdc4c698343192143b2b421": {
+      "model_module": "@jupyter-widgets/base",
+      "model_module_version": "1.1.0",
+      "model_name": "LayoutModel",
+      "state": {
+       "height": "auto",
+       "width": "auto"
+      }
+     },
+     "ad9f1c5a27414203996ec7d5d9ae696b": {
+      "model_module": "ipysheet",
+      "model_module_version": "~0.4.1",
+      "model_name": "RendererModel",
+      "state": {
+       "_view_module": "ipysheet",
+       "_view_module_version": "~0.4.1",
+       "code": "\nfunction() {\n                  var the_renderer;\n                the_renderer = function flx_the_renderer (value) {\n                    return ({backgroundColor: ((value < 0))? (\"orange\") : (\"\")});\n                };\n\n  return the_renderer\n\n}()\n",
+       "name": "negative_transpiled"
+      }
+     },
+     "aefbc5694c834e6c9d5d86696b28c512": {
       "model_module": "ipysheet",
       "model_module_version": "~0.4.1",
       "model_name": "SheetModel",
       "state": {
-       "cells": [
-        "IPY_MODEL_078a93ab3a954e6e9fd0cb309683ad9a"
-       ],
-       "layout": "IPY_MODEL_bfa652564a4041be993c7b9861a94fa2"
+       "columns": 5,
+       "layout": "IPY_MODEL_d377c608b55842f4b97ee5ed2ac0815c",
+       "rows": 5
       }
      },
-     "9ed9cb9f61294fb0b9a97848d193c1db": {
+     "b1c054ac2a1340fb9200c5f16af5323e": {
+      "model_module": "@jupyter-widgets/base",
+      "model_module_version": "1.1.0",
+      "model_name": "LayoutModel",
+      "state": {}
+     },
+     "b33250fe84c84ed4adc564398824e817": {
+      "model_module": "@jupyter-widgets/base",
+      "model_module_version": "1.1.0",
+      "model_name": "LayoutModel",
+      "state": {
+       "height": "auto",
+       "width": "auto"
+      }
+     },
+     "b37b8eca5c8848be89723324f2d00cc9": {
       "model_module": "ipysheet",
       "model_module_version": "~0.4.1",
       "model_name": "SheetModel",
       "state": {
        "cells": [
-        "IPY_MODEL_f0faccde3e71426a96bf6a454802b5dd",
-        "IPY_MODEL_bf3490b9d1f948c3ab227bc5d8bb5d23",
-        "IPY_MODEL_535bb3899bcf426389df0a9ed97c4e3d",
-        "IPY_MODEL_d860be8268d9499ba20855a4d1eaac84",
-        "IPY_MODEL_6476661bcf82408dbc65f220605068dc",
-        "IPY_MODEL_a6ee3cb412cf4bd3b88fcc68accb532e"
+        "IPY_MODEL_cf3f654a13ac44a480f482b9c7255d5b",
+        "IPY_MODEL_5902bfe2b33b44dda27c63383745a6b8",
+        "IPY_MODEL_b5f0019090854f9eb8b09fc43c10f91a"
        ],
-       "column_headers": false,
-       "columns": 2,
-       "layout": "IPY_MODEL_1f92a18646e94c68b9424fdbc6bff1f4",
-       "row_headers": false
+       "layout": "IPY_MODEL_b33250fe84c84ed4adc564398824e817",
+       "rows": 5
       }
      },
-     "a6ee3cb412cf4bd3b88fcc68accb532e": {
-      "model_module": "ipysheet",
-      "model_module_version": "~0.4.1",
-      "model_name": "CellRangeModel",
+     "b3cdf33d93784df695183e0fe55efe3e": {
+      "model_module": "@jupyter-widgets/base",
+      "model_module_version": "1.1.0",
+      "model_name": "LayoutModel",
       "state": {
-       "_view_module": null,
-       "_view_module_version": "",
-       "column_end": 0,
-       "column_start": 0,
-       "row_end": 2,
-       "row_start": 2,
-       "style": {
-        "fontWeight": "bold"
-       },
-       "type": "text",
-       "value": "sum"
+       "height": "auto",
+       "width": "auto"
       }
      },
-     "a8546559d0c544af840ac5212b3fe9fd": {
+     "b5f0019090854f9eb8b09fc43c10f91a": {
       "model_module": "ipysheet",
       "model_module_version": "~0.4.1",
       "model_name": "CellRangeModel",
@@ -862,7 +884,7 @@
        ]
       }
      },
-     "aa085b146c2241c0929ced4f8d0b8cc3": {
+     "ba619725ce96426ead50b7d9321b08f6": {
       "model_module": "ipysheet",
       "model_module_version": "~0.4.1",
       "model_name": "CellRangeModel",
@@ -873,42 +895,11 @@
        "column_start": 0,
        "row_end": 0,
        "row_start": 0,
-       "style": {
-        "fontWeight": "bold"
-       },
        "type": "text",
-       "value": "a"
-      }
-     },
-     "ae4747feb81646a8bf093db1b62ed0a8": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "1.4.0",
-      "model_name": "LinkModel",
-      "state": {
-       "source": [
-        "IPY_MODEL_b1fde7c30c954ad8b0198bc66b28a121",
-        "value"
-       ],
-       "target": [
-        "IPY_MODEL_2c4fa222b61a4d518c6a40c92b040f11",
-        "value"
-       ]
-      }
-     },
-     "b1fde7c30c954ad8b0198bc66b28a121": {
-      "model_module": "ipysheet",
-      "model_module_version": "~0.4.1",
-      "model_name": "CellRangeModel",
-      "state": {
-       "_view_module": null,
-       "_view_module_version": "",
-       "row_end": 0,
-       "row_start": 0,
-       "type": "numeric",
-       "value": 1
+       "value": "Hello"
       }
      },
-     "ba0c6a1a21624d82aa23f75afdc7666c": {
+     "bcbafc1b29b749ba809ce88c98e382e7": {
       "model_module": "ipysheet",
       "model_module_version": "~0.4.1",
       "model_name": "CellRangeModel",
@@ -924,34 +915,57 @@
        "value": "b"
       }
      },
-     "bf3490b9d1f948c3ab227bc5d8bb5d23": {
+     "bf2fa263e1044e1eb082865be4d25eca": {
+      "model_module": "@jupyter-widgets/base",
+      "model_module_version": "1.1.0",
+      "model_name": "LayoutModel",
+      "state": {}
+     },
+     "c55becb64db14d5fb42adf386a40d0ef": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "1.4.0",
+      "model_name": "VBoxModel",
+      "state": {
+       "children": [
+        "IPY_MODEL_51ebae69061f4846816261b35ae62b32",
+        "IPY_MODEL_e8882d237be147c190d87e8fb3564121"
+       ],
+       "layout": "IPY_MODEL_bf2fa263e1044e1eb082865be4d25eca"
+      }
+     },
+     "cf3f654a13ac44a480f482b9c7255d5b": {
       "model_module": "ipysheet",
       "model_module_version": "~0.4.1",
       "model_name": "CellRangeModel",
       "state": {
        "_view_module": null,
        "_view_module_version": "",
-       "column_end": 0,
+       "column_end": 3,
        "column_start": 0,
        "row_end": 0,
        "row_start": 0,
+       "squeeze_column": false,
        "style": {
-        "fontWeight": "bold"
+        "backgroundColor": "red"
        },
-       "type": "text",
-       "value": "a"
+       "type": "int",
+       "value": [
+        0,
+        1,
+        2,
+        3
+       ]
       }
      },
-     "bfa652564a4041be993c7b9861a94fa2": {
-      "model_module": "@jupyter-widgets/base",
-      "model_module_version": "1.1.0",
-      "model_name": "LayoutModel",
+     "d11ccb31354249589dd350497d7c0779": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "1.4.0",
+      "model_name": "SliderStyleModel",
       "state": {
-       "height": "auto",
-       "width": "auto"
+       "description_width": ""
       }
      },
-     "c1dbe91c4db244ceb857f8ce9401cc6a": {
+     "d377c608b55842f4b97ee5ed2ac0815c": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "1.1.0",
       "model_name": "LayoutModel",
@@ -960,22 +974,20 @@
        "width": "auto"
       }
      },
-     "c5cb3daa341842a8a77d33bdaed0d179": {
+     "d46df184a60c4a67a4e6147de0d75f54": {
       "model_module": "ipysheet",
       "model_module_version": "~0.4.1",
       "model_name": "CellRangeModel",
       "state": {
        "_view_module": null,
        "_view_module_version": "",
-       "column_end": 2,
-       "column_start": 2,
-       "row_end": 2,
-       "row_start": 2,
-       "type": "numeric",
-       "value": 42
+       "row_end": 0,
+       "row_start": 0,
+       "type": "int",
+       "value": 1
       }
      },
-     "d860be8268d9499ba20855a4d1eaac84": {
+     "e665dc60260d43029ff6c9f009bc71ca": {
       "model_module": "ipysheet",
       "model_module_version": "~0.4.1",
       "model_name": "CellRangeModel",
@@ -984,82 +996,69 @@
        "_view_module_version": "",
        "column_end": 0,
        "column_start": 0,
+       "row_end": 0,
+       "row_start": 0,
        "style": {
         "fontWeight": "bold"
        },
        "type": "text",
-       "value": "b"
+       "value": "a"
       }
      },
-     "d91e09a8701e4888a34550824908ab8c": {
+     "e755bf96293344d6b58f964663157da8": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "1.1.0",
       "model_name": "LayoutModel",
-      "state": {}
-     },
-     "dc5faebcb39a46b4bab9fe1d6ac59dd1": {
-      "model_module": "ipysheet",
-      "model_module_version": "~0.4.1",
-      "model_name": "SheetModel",
       "state": {
-       "cells": [
-        "IPY_MODEL_7096b52219184bbb99b0e8c2a834fcbb",
-        "IPY_MODEL_7e19d6589d564fcca765396f70c0b799",
-        "IPY_MODEL_c5cb3daa341842a8a77d33bdaed0d179"
-       ],
-       "layout": "IPY_MODEL_155748346e0a4bfbaa4a6cdd209755f5"
+       "height": "auto",
+       "width": "auto"
       }
      },
-     "e93dd6c4fb4240478c3cbb535bf3d478": {
-      "model_module": "ipysheet",
-      "model_module_version": "~0.4.1",
-      "model_name": "CellRangeModel",
+     "e8882d237be147c190d87e8fb3564121": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "1.4.0",
+      "model_name": "FloatSliderModel",
       "state": {
-       "_view_module": null,
-       "_view_module_version": "",
-       "row_end": 4,
-       "squeeze_row": false,
-       "style": {
-        "backgroundColor": "green"
-       },
-       "type": "text",
-       "value": [
-        "a",
-        "b",
-        "c",
-        "d"
-       ]
+       "description": "a",
+       "layout": "IPY_MODEL_136070030dee469a91c0b5f86f8a744b",
+       "max": 10,
+       "min": -10,
+       "step": 0.1,
+       "style": "IPY_MODEL_567b271aa9b54533a75d50c63da111f5",
+       "value": 1
       }
      },
-     "ee569f56091c4b069b0ee13367c33a60": {
+     "eeed7f4571194d48a2af3c241722653a": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "1.4.0",
-      "model_name": "VBoxModel",
+      "model_name": "LinkModel",
       "state": {
-       "children": [
-        "IPY_MODEL_593c55e36b1e449fba9193764c1b00ce",
-        "IPY_MODEL_2c4fa222b61a4d518c6a40c92b040f11"
+       "source": [
+        "IPY_MODEL_d46df184a60c4a67a4e6147de0d75f54",
+        "value"
        ],
-       "layout": "IPY_MODEL_f099a6b43c1c4a009f8b06dbb068c287"
+       "target": [
+        "IPY_MODEL_02cee59ebef44b7cabddc13e7250526c",
+        "value"
+       ]
       }
      },
-     "f099a6b43c1c4a009f8b06dbb068c287": {
-      "model_module": "@jupyter-widgets/base",
-      "model_module_version": "1.1.0",
-      "model_name": "LayoutModel",
-      "state": {}
-     },
-     "f0faccde3e71426a96bf6a454802b5dd": {
+     "f1ae488f0a9245938c107a68dcf959bd": {
       "model_module": "ipysheet",
       "model_module_version": "~0.4.1",
       "model_name": "CellRangeModel",
       "state": {
        "_view_module": null,
        "_view_module_version": "",
+       "column_end": 0,
+       "column_start": 0,
        "row_end": 0,
        "row_start": 0,
-       "type": "numeric",
-       "value": 1
+       "style": {
+        "fontWeight": "bold"
+       },
+       "type": "text",
+       "value": "a"
       }
      }
     },
diff --git a/examples/format.ipynb b/examples/format.ipynb
index 5bf56d0..3820ef5 100644
--- a/examples/format.ipynb
+++ b/examples/format.ipynb
@@ -16,14 +16,21 @@
    "outputs": [],
    "source": [
     "sheet = ipysheet.sheet()\n",
-    "cell0 = ipysheet.cell(0, 0, 0, numeric_format='0.0', type='numeric')\n",
+    "cell0 = ipysheet.cell(0, 0, 0, numeric_format='.2', type='float')\n",
     "cell1 = ipysheet.cell(1, 0, \"Hello\", type='text')\n",
-    "cell2 = ipysheet.cell(0, 1, 0.1, numeric_format='0.000', type='numeric')\n",
-    "cell3 = ipysheet.cell(1, 1, 15.9, numeric_format='0.00', type='numeric')\n",
+    "cell2 = ipysheet.cell(0, 1, 10000000000, numeric_format='e', type='int')\n",
+    "cell3 = ipysheet.cell(1, 1, 5.91234314, numeric_format='.4', type='float')\n",
     "cell4 = ipysheet.cell(2, 2, \"02/14/2019\", date_format='MM/DD/YYYY', type='date')\n",
     "\n",
     "sheet"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
diff --git a/ipysheet/easy.py b/ipysheet/easy.py
index 4f2f4a3..f16e47d 100644
--- a/ipysheet/easy.py
+++ b/ipysheet/easy.py
@@ -5,7 +5,6 @@
 """
 __all__ = ['sheet', 'current', 'cell', 'calculation', 'row', 'column', 'cell_range', 'hold_cells', 'renderer']
 
-import numbers
 import six
 from contextlib import contextmanager
 
@@ -23,15 +22,16 @@
 
 _common_doc = {
     'args': """
-        type (string): Type of cell, options are: text, numeric, checkbox, dropdown, numeric, date, widget.
+        type (string): Type of cell, options are: text, int, float, checkbox, dropdown, date, widget.
             If type is None, the type is inferred from the type of the value being passed,
-            numeric (float or int type), boolean (bool type), widget (any widget object), or else text.
+            float, int, boolean (bool type), widget (any widget object), or else text.
             When choice is given the type will be assumed to be dropdown.
             The types refer (currently) to the handsontable types: https://handsontable.com/docs/6.2.2/demo-custom-renderers.html
         color (string): The text color in the cell
         background_color (string): The background color in the cell
         read_only (bool): Whether the cell is editable or not
-        numeric_format (string): Numbers format
+        numeric_format (ipywidgets.widgets.trait_types.NumberFormat): Numbers format, default is 'd' for int cells, '.2f' for
+            float cells
         date_format (string): Dates format
         time_format (string): Time format
         renderer (string): Renderer name to use for the cell
@@ -95,7 +95,7 @@ def current():
 @doc_subst(_common_doc)
 def cell(row, column, value=0., type=None, color=None, background_color=None,
          font_style=None, font_weight=None, style=None, label_left=None, choice=None,
-         read_only=False, numeric_format='0.000', date_format='YYYY/MM/DD', renderer=None, **kwargs):
+         read_only=False, numeric_format=None, date_format='YYYY/MM/DD', renderer=None, **kwargs):
     """Adds a new ``Cell`` widget to the current ``Sheet``
 
     Args:
@@ -111,7 +111,8 @@ def cell(row, column, value=0., type=None, color=None, background_color=None,
         >>> from ipysheet import sheet, cell
         >>>
         >>> s1 = sheet()
-        >>> cell(0, 0, 36.)            # The Cell type will be 'numeric'
+        >>> cell(0, 0, 36)             # The Cell type will be 'int'
+        >>> cell(0, 0, 36.3)           # The Cell type will be 'float'
         >>> cell(1, 0, True)           # The Cell type will be 'checkbox'
         >>> cell(0, 1, 'Hello World!') # The Cell type will be 'text'
         >>> c = cell(1, 1, True)
@@ -121,8 +122,10 @@ def cell(row, column, value=0., type=None, color=None, background_color=None,
     if type is None:
         if isinstance(value, bool):
             type = 'checkbox'
-        elif isinstance(value, numbers.Number):
-            type = 'numeric'
+        elif isinstance(value, int):
+            type = 'int'
+        elif isinstance(value, float):
+            type = 'float'
         elif isinstance(value, widgets.Widget):
             type = 'widget'
         else:
@@ -157,7 +160,7 @@ def cell(row, column, value=0., type=None, color=None, background_color=None,
 @doc_subst(_common_doc)
 def row(row, value, column_start=0, column_end=None, type=None, color=None, background_color=None,
         font_style=None, font_weight=None, style=None, choice=None,
-        read_only=False, numeric_format='0.000', date_format='YYYY/MM/DD', renderer=None, **kwargs):
+        read_only=False, numeric_format=None, date_format='YYYY/MM/DD', renderer=None, **kwargs):
     """Create a ``Cell`` widget, representing multiple cells in a sheet, in a horizontal row
 
     Args:
@@ -187,7 +190,7 @@ def row(row, value, column_start=0, column_end=None, type=None, color=None, back
 @doc_subst(_common_doc)
 def column(column, value, row_start=0, row_end=None, type=None, color=None, background_color=None,
            font_style=None, font_weight=None, style=None, choice=None,
-           read_only=False, numeric_format='0.000', date_format='YYYY/MM/DD', renderer=None, **kwargs):
+           read_only=False, numeric_format=None, date_format='YYYY/MM/DD', renderer=None, **kwargs):
     """Create a ``Cell`` widget, representing multiple cells in a sheet, in a vertical column
 
     Args:
@@ -219,7 +222,7 @@ def cell_range(value,
                row_start=0, column_start=0, row_end=None, column_end=None, transpose=False,
                squeeze_row=False, squeeze_column=False, type=None, color=None, background_color=None,
                font_style=None, font_weight=None, style=None, choice=None,
-               read_only=False, numeric_format='0.000', date_format='YYYY/MM/DD', renderer=None, **kwargs):
+               read_only=False, numeric_format=None, date_format='YYYY/MM/DD', renderer=None, **kwargs):
     """Create a ``Cell`` widget, representing multiple cells in a sheet
 
     Args:
@@ -278,7 +281,8 @@ def cell_range(value,
     # see if we an infer a type from the data, otherwise leave it None
     if type is None:
         type_check_map = [('checkbox', lambda x: isinstance(x, bool)),
-                          ('numeric', lambda x: isinstance(x, numbers.Number)),
+                          ('int', lambda x: isinstance(x, int)),
+                          ('float', lambda x: isinstance(x, float) or isinstance(x, int)),
                           ('text', lambda x: isinstance(x, six.string_types)),
                           ('widget', lambda x: isinstance(x, widgets.Widget)),
                           ]
diff --git a/ipysheet/numpy_loader.py b/ipysheet/numpy_loader.py
index c7870f2..f1de927 100644
--- a/ipysheet/numpy_loader.py
+++ b/ipysheet/numpy_loader.py
@@ -1,5 +1,5 @@
 from .easy import sheet, column, cell_range
-from .utils import extract_data, get_cell_type, get_cell_numeric_format
+from .utils import extract_data, get_cell_type
 
 
 def from_array(array):
@@ -27,7 +27,6 @@ def from_array(array):
     columns = 1 if len(array.shape) == 1 else array.shape[1]
 
     kwargs = {
-        'numeric_format': get_cell_numeric_format(array.dtype),
         'type': get_cell_type(array.dtype)
     }
 
diff --git a/ipysheet/pandas_loader.py b/ipysheet/pandas_loader.py
index 17140f6..544a3f2 100644
--- a/ipysheet/pandas_loader.py
+++ b/ipysheet/pandas_loader.py
@@ -1,5 +1,5 @@
 from .sheet import Cell, Sheet
-from .utils import extract_data, get_cell_numeric_format, get_cell_type
+from .utils import extract_data, get_cell_type
 
 
 def _format_date(date):
@@ -56,7 +56,6 @@ def from_dataframe(dataframe):
             column_start=idx,
             column_end=idx,
             type=get_cell_type(arr.dtype),
-            numeric_format=get_cell_numeric_format(arr.dtype),
             squeeze_row=False,
             squeeze_column=True
         ))
diff --git a/ipysheet/sheet.py b/ipysheet/sheet.py
index 5e17f01..37986ca 100644
--- a/ipysheet/sheet.py
+++ b/ipysheet/sheet.py
@@ -1,5 +1,6 @@
 import ipywidgets as widgets
 from ipywidgets.widgets.widget_layout import LayoutTraitType
+from ipywidgets.widgets.trait_types import NumberFormat
 
 import traitlets
 from traitlets import Unicode, CInt, List, Tuple, Instance, Union, Dict, Bool, Any
@@ -33,7 +34,7 @@ class Cell(widgets.Widget):
     squeeze_column = Bool(True).tag(sync=True)
     transpose = Bool(False).tag(sync=True)
     choice = List(Unicode(), allow_none=True, default_value=None).tag(sync=True)
-    numeric_format = Unicode('0.000', allow_none=True).tag(sync=True)
+    numeric_format = NumberFormat(None, allow_none=True).tag(sync=True)
     date_format = Unicode('YYYY/MM/DD', allow_none=True).tag(sync=True)
     time_format = Unicode('h:mm:ss a', allow_none=True).tag(sync=True)
 
diff --git a/ipysheet/test_all.py b/ipysheet/test_all.py
index f780ca9..546e4bd 100644
--- a/ipysheet/test_all.py
+++ b/ipysheet/test_all.py
@@ -276,10 +276,10 @@ def test_cell_values():
 
     cell = ipysheet.cell(0, 0, value=1.2)
     assert cell.value == 1.2
-    assert cell.type == 'numeric'
+    assert cell.type == 'float'
     cell = ipysheet.cell(0, 0, value=1)
     assert cell.value == 1
-    assert cell.type == 'numeric'
+    assert cell.type == 'int'
 
     cell = ipysheet.Cell(value='1.2')
     assert cell.value == '1.2'
@@ -291,18 +291,18 @@ def test_cell_values():
 
     cell = ipysheet.row(0, [0, 1.2])
     assert cell.value == [0, 1.2]
-    assert cell.type == 'numeric'
+    assert cell.type == 'float'
 
     cell = ipysheet.row(0, [0, 1])
     assert cell.value == [0, 1]
-    assert cell.type == 'numeric'
+    assert cell.type == 'int'
 
     cell = ipysheet.row(0, ['a', 'b'])
     assert cell.value == ['a', 'b']
     assert cell.type == 'text'
 
     cell = ipysheet.row(0, [True, 0])
-    assert cell.type == 'numeric'
+    assert cell.type == 'int'
 
     cell = ipysheet.row(0, [True, 'bla'])
     assert cell.type is None
@@ -442,12 +442,12 @@ def test_from_dataframe():
     sheet = ipysheet.from_dataframe(df)
     assert len(sheet.cells) == 7
     assert sheet.cells[0].value == [1., 1., 1., 1.]
-    assert sheet.cells[0].type == 'numeric'
+    assert sheet.cells[0].type == 'float'
     assert sheet.cells[1].value == [None, '2013/01/02', None, '2013/01/02']
     assert sheet.cells[1].type == 'date'
     assert sheet.cells[2].value == [1., 1., 1., 1.]
-    assert sheet.cells[2].type == 'numeric'
-    assert sheet.cells[2].numeric_format == '0.000'
+    assert sheet.cells[2].type == 'float'
+    assert sheet.cells[2].numeric_format is None
     assert sheet.cells[3].value == [False, True, False, False]
     assert sheet.cells[3].type == 'checkbox'
     assert sheet.cells[4].value == ['test', 'train', 'test', 'train']
@@ -455,8 +455,8 @@ def test_from_dataframe():
     assert sheet.cells[5].value == ['foo', 'foo', 'foo', 'foo']
     assert sheet.cells[5].type == 'text'
     assert sheet.cells[6].value == [0, 3, 9, 18]
-    assert sheet.cells[6].type == 'numeric'
-    assert sheet.cells[6].numeric_format == '0[.]0'
+    assert sheet.cells[6].type == 'int'
+    assert sheet.cells[6].numeric_format is None
 
 
 def test_from_to_dataframe():
@@ -503,7 +503,7 @@ def test_from_array():
     arr = np.random.randn(6, 10)
     sheet = ipysheet.from_array(arr)
     assert len(sheet.cells) == 1
-    assert sheet.cells[0].type == 'numeric'
+    assert sheet.cells[0].type == 'float'
     assert sheet.cells[0].value is arr
     assert sheet.rows == 6
     assert sheet.columns == 10
diff --git a/ipysheet/utils.py b/ipysheet/utils.py
index e1125be..43bdf22 100644
--- a/ipysheet/utils.py
+++ b/ipysheet/utils.py
@@ -50,24 +50,15 @@ def extract_data(sheet):
 
 
 def get_cell_type(dt):
-    # TODO Differentiate integer and float? Using custom renderers and
-    # validators for integers?
     # Add support for void type from NumPy?
     # See https://handsontable.com/docs/6.2.2/tutorial-cell-types.html
     return {
         'b': 'checkbox',
-        'i': 'numeric',
-        'u': 'numeric',
-        'f': 'numeric',
-        'm': 'numeric',
+        'i': 'int',
+        'u': 'int',
+        'f': 'float',
+        'm': 'float',
         'M': 'date',
         'S': 'text',
         'U': 'text'
     }.get(dt.kind, 'text')
-
-
-def get_cell_numeric_format(dt):
-    return {
-        'i': '0[.]0',
-        'f': '0.000',
-    }.get(dt.kind)
diff --git a/js/src/sheet.ts b/js/src/sheet.ts
index 95e986c..8938b89 100644
--- a/js/src/sheet.ts
+++ b/js/src/sheet.ts
@@ -1,4 +1,5 @@
-import * as widgets  from '@jupyter-widgets/base';
+import * as widgets from '@jupyter-widgets/base';
+import * as d3 from 'd3-format';
 import {cloneDeep, extend, includes as contains, each, debounce, times, map, unzip as transpose} from 'lodash';
 import {semver_range} from './version';
 import {RendererModel} from './renderer';
@@ -35,7 +36,7 @@ let CellRangeModel = widgets.WidgetModel.extend({
             squeeze_row: true,
             squeeze_column: true,
             transpose: false,
-            numeric_format: '0.000',
+            numeric_format: null,
             date_format: 'YYYY/MM/DD',
             time_format: 'h:mm:ss a'
         });
@@ -143,8 +144,8 @@ let SheetModel = widgets.DOMWidgetModel.extend({
                     cell_data.options['readOnly'] = cell.get('read_only');
                 if (cell.get('choice') != null)
                     cell_data.options['source'] = cell.get('choice')
-                if (cell.get('numeric_format') && cell.get('type') == 'numeric')
-                    cell_data.options['numericFormat'] = {'pattern': cell.get('numeric_format')};
+                if (cell.get('numeric_format') && (cell.get('type') == 'int' || cell.get('type') == 'float'))
+                    cell_data.options['numericFormat'] = cell.get('numeric_format');
                 if (cell.get('date_format') && cell.get('type') == 'date') {
                     cell_data.options['correctFormat'] = true;
                     cell_data.options['dateFormat'] = cell.get('date_format') || cell_data.options['dateFormat'];
@@ -262,7 +263,7 @@ let put_values2d = function(grid, values) {
     }
 };
 
-// calls the original renderer and then applies custom styling
+// Custom styled renderer that applies the default renderer then apply the given style on the cell
 (Handsontable.renderers as any).registerRenderer('styled', function customRenderer(hotInstance, td, row, column, prop, value, cellProperties) {
     let name = cellProperties.original_renderer || cellProperties.type || 'text';
     let original_renderer = (Handsontable.renderers as any).getRenderer(name);
@@ -272,6 +273,52 @@ let put_values2d = function(grid, values) {
     });
 });
 
+
+// Register `int` and `float` cell types
+class IntEditor extends Handsontable.editors.TextEditor {
+    getValue() {
+        return parseInt(this.TEXTAREA.value);
+    }
+};
+
+function int_renderer(hotInstance, td, row, column, prop, value, cellProperties) {
+    const numeric_format = cellProperties.numericFormat || 'd';
+    td.innerHTML = d3.format(numeric_format)(value);
+}
+
+function int_validator(query, callback) {
+    callback(Number.isInteger(query));
+}
+
+(Handsontable.cellTypes as any).registerCellType('int', {
+    editor: IntEditor,
+    renderer: int_renderer,
+    validator: int_validator,
+    allowInvalid: false
+});
+
+class FloatEditor extends Handsontable.editors.TextEditor {
+    getValue() {
+        return parseFloat(this.TEXTAREA.value);
+    }
+};
+
+function float_renderer(hotInstance, td, row, column, prop, value, cellProperties) {
+    const numeric_format = cellProperties.numericFormat || '.2f';
+    td.innerHTML = d3.format(numeric_format)(value);
+}
+
+function float_validator(query, callback) {
+    callback(typeof query == 'number');
+}
+
+(Handsontable.cellTypes as any).registerCellType('float', {
+    editor: FloatEditor,
+    renderer: float_renderer,
+    validator: float_validator,
+    allowInvalid: false
+});
+
 let SheetView = widgets.DOMWidgetView.extend({
     render: function() {
         // this.widget_view_promises = {}
diff --git a/js/src/test/test_sheet.ts b/js/src/test/test_sheet.ts
index a634933..8294169 100644
--- a/js/src/test/test_sheet.ts
+++ b/js/src/test/test_sheet.ts
@@ -147,12 +147,12 @@ describe('sheet', function() {
         expect(data[1][2].value, 'when cell.value is change').to.equal(999);
     })
     it('numeric cell with value zero should indeed have value zero', async function() {
-        await make_cell.apply(this, [{value: 0.00, type:'numeric'}]);
+        await make_cell.apply(this, [{value: 0.00, type:'float'}]);
         var data = this.sheet.data;
-        expect(data[1][2].value, 'for initial value').to.equal(0);
+        expect(data[1][2].value, 'for initial value').to.equal(0.0);
     })
     it('none cell with should be set', async function() {
-        var cell = await make_cell.apply(this, [{value: 0.00, type:'numeric'}]);
+        var cell = await make_cell.apply(this, [{value: 0.00, type:'float'}]);
         var data = this.sheet.data;
         expect(data[1][2].value, 'for initial value').to.equal(0);
         cell.set('value', null);
diff --git a/js/tsconfig.json b/js/tsconfig.json
index a2b14b4..478bd7d 100644
--- a/js/tsconfig.json
+++ b/js/tsconfig.json
@@ -1,7 +1,7 @@
 {
 "compilerOptions": {
     "noImplicitAny": false,
-    "lib": ["dom", "es5", "es2015.promise", "es2015.iterable"],
+    "lib": ["dom", "es5", "es2015"],
     "strictNullChecks": true,
     "module": "commonjs",
     "moduleResolution": "node",