# Column Toggling Use the **Columns** dropdown in the toolbar to show/hide columns. # Wide Table This table has 16 columns -- try hiding some:
TableRows10Columns16
Wide Metrics Table
id i64
metric_001 f64
metric_002 f64
metric_003 f64
metric_004 f64
metric_005 f64
metric_006 f64
metric_007 f64
metric_008 f64
metric_009 f64
metric_010 f64
metric_011 f64
metric_012 f64
metric_013 f64
metric_014 f64
metric_015 f64
0 0 -0.256 0.395 0.305 -0.62 -0.808 0.497 0.615 1.443 0.246 -1.974 0.325 1.465 -0.787 0.573 -0.337
1 1 0.511 0.185 -0.046 -0.74 0.245 -0.062 -0.612 0.578 0.434 -0.634 0.65 -0.445 0.632 0.001 0.386
2 2 -0.226 -1.666 0.521 -0.344 0.427 -1.465 -0.453 -1.9 1.594 0.842 0.12 -1.38 1.129 0.764 1.837
3 3 -0.315 0.855 -0.642 -0.106 -1.49 0.828 -1.265 -2.518 0.619 -1.811 1.146 -0.135 0.859 0.566 -2.565
4 4 -0.93 0.506 0.309 0.632 0.048 0.669 -0.968 0.357 0.519 -0.184 -0.662 -0.149 0.345 2.011 -1.124
5 5 -0.213 0.499 0.394 0.248 1.306 0.946 -0.531 -0.736 0.548 1.02 -0.415 -0.298 0.142 0.325 0.244
6 6 1.112 -1.691 -0.661 -0.447 -2.014 1.441 1.289 -1.12 -1.568 -1.311 1.042 1.405 0.152 -0.428 0.398
7 7 0.424 -1.744 1.718 -0.957 -0.322 0.362 -2.032 0.977 1.282 1.61 0.027 -1.027 0.575 -0.373 0.239
8 8 1.037 -0.89 0.557 -0.521 -0.106 0.119 -1.458 1.102 0.955 0.552 -0.88 1.261 -0.176 -0.013 -0.431
9 9 0.249 -0.468 1.197 1.221 -0.817 -1.299 0.239 0.157 0.53 -0.15 0.946 -1.268 0.277 0.924 0.655
# Column Subset Pre-select specific columns with `columns=`:
TableRows12Columns5
Cities -- 3 columns only
city str
country str
population i64
0 Tokyo Japan 13960000
1 Paris France 2161000
2 New York USA 8336000
3 London UK 8982000
4 Sydney Australia 5312000
5 Berlin Germany 3645000
6 Mumbai India 20411000
7 São Paulo Brazil 12330000
8 Cairo Egypt 10230000
9 Toronto Canada 2930000
# Toggle Disabled Set `column_toggle=False` to remove the dropdown:
TableRows12Columns5
No column toggle
city str
country str
population i64
latitude f64
longitude f64
0 Tokyo Japan 13960000 35.6762 139.6503
1 Paris France 2161000 48.8566 2.3522
2 New York USA 8336000 40.7128 -74.006
3 London UK 8982000 51.5074 -0.1278
4 Sydney Australia 5312000 -33.8688 151.2093
5 Berlin Germany 3645000 52.52 13.405
6 Mumbai India 20411000 19.076 72.8777
7 São Paulo Brazil 12330000 -23.5505 -46.6333
8 Cairo Egypt 10230000 30.0444 31.2357
9 Toronto Canada 2930000 43.6532 -79.3832