.tb-container .tb-container-inner{width:100%;margin:0 auto} .wp-block-toolset-blocks-container.tb-container[data-toolset-blocks-container="b1f9aa973d3d82ce7f31eb393f7dbeaa"] { padding: 25px 15% 25px 10%; } .tb-grid,.tb-grid>.block-editor-inner-blocks>.block-editor-block-list__layout{display:grid;grid-row-gap:25px;grid-column-gap:25px}.tb-grid-item{background:#d38a03;padding:30px}.tb-grid-column{flex-wrap:wrap}.tb-grid-column>*{width:100%}.tb-grid-column.tb-grid-align-top{width:100%;display:flex;align-content:flex-start}.tb-grid-column.tb-grid-align-center{width:100%;display:flex;align-content:center}.tb-grid-column.tb-grid-align-bottom{width:100%;display:flex;align-content:flex-end} .wpv-view-output[data-toolset-views-view-editor="ea2f4f58762e1e2ab75c472323b7d44c"] > .tb-grid-column:nth-of-type(3n + 1) { grid-column: 1 } .wpv-view-output[data-toolset-views-view-editor="ea2f4f58762e1e2ab75c472323b7d44c"] > .tb-grid-column:nth-of-type(3n + 2) { grid-column: 2 } .wpv-view-output[data-toolset-views-view-editor="ea2f4f58762e1e2ab75c472323b7d44c"] > .tb-grid-column:nth-of-type(3n + 3) { grid-column: 3 } .wpv-view-output[data-toolset-views-view-editor="ea2f4f58762e1e2ab75c472323b7d44c"] .js-wpv-loop-wrapper > .tb-grid { grid-template-columns: minmax(0, 0.3333fr) minmax(0, 0.3333fr) minmax(0, 0.3333fr);grid-auto-flow: row } .wpv-pagination-nav-links[data-toolset-views-view-pagination-block="8bdb78819481bf533e780b9c5d859057"] { text-align: left;justify-content: flex-start; } .wpv-block-loop-item[data-toolset-views-view-template-block="f5892b31d2df633c228ddcae32317031"] { margin-bottom: 10px; } .tb-grid,.tb-grid>.block-editor-inner-blocks>.block-editor-block-list__layout{display:grid;grid-row-gap:25px;grid-column-gap:25px}.tb-grid-item{background:#d38a03;padding:30px}.tb-grid-column{flex-wrap:wrap}.tb-grid-column>*{width:100%}.tb-grid-column.tb-grid-align-top{width:100%;display:flex;align-content:flex-start}.tb-grid-column.tb-grid-align-center{width:100%;display:flex;align-content:center}.tb-grid-column.tb-grid-align-bottom{width:100%;display:flex;align-content:flex-end} .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="8fefe44b785313878017165815738677"] { padding: 0px 0px 0px 15px;margin: 0px;grid-template-columns: minmax(0, 0.6fr) minmax(0, 0.4fr);grid-auto-flow: row } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="8fefe44b785313878017165815738677"] > .tb-grid-column:nth-of-type(2n + 1) { grid-column: 1 } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="8fefe44b785313878017165815738677"] > .tb-grid-column:nth-of-type(2n + 2) { grid-column: 2 } .wp-block-toolset-blocks-grid-column.tb-grid-column[data-toolset-blocks-grid-column="3034fbe886c11054e95b46b09d3e4112"] { display: flex; } .tb-fields-and-text[data-toolset-blocks-fields-and-text="33a2aef42d823f8eae97b7cc27755424"] { font-size: 16px; } .tb-fields-and-text[data-toolset-blocks-fields-and-text="33a2aef42d823f8eae97b7cc27755424"] p { font-size: 16px; } .tb-fields-and-text[data-toolset-blocks-fields-and-text="4b580cc7c7816a512deb848c3f89825b"] { font-size: 30px; } .tb-fields-and-text[data-toolset-blocks-fields-and-text="4b580cc7c7816a512deb848c3f89825b"] p { font-size: 30px; } .tb-fields-and-text[data-toolset-blocks-fields-and-text="1a72a82680f6b9936daf6a35d2250e9e"] { margin-top: 15px;margin-right: 50px;margin-left: 50px; } @media only screen and (max-width: 781px) { .tb-container .tb-container-inner{width:100%;margin:0 auto}.tb-grid,.tb-grid>.block-editor-inner-blocks>.block-editor-block-list__layout{display:grid;grid-row-gap:25px;grid-column-gap:25px}.tb-grid-item{background:#d38a03;padding:30px}.tb-grid-column{flex-wrap:wrap}.tb-grid-column>*{width:100%}.tb-grid-column.tb-grid-align-top{width:100%;display:flex;align-content:flex-start}.tb-grid-column.tb-grid-align-center{width:100%;display:flex;align-content:center}.tb-grid-column.tb-grid-align-bottom{width:100%;display:flex;align-content:flex-end} .wpv-view-output[data-toolset-views-view-editor="ea2f4f58762e1e2ab75c472323b7d44c"] > .tb-grid-column:nth-of-type(3n + 1) { grid-column: 1 } .wpv-view-output[data-toolset-views-view-editor="ea2f4f58762e1e2ab75c472323b7d44c"] > .tb-grid-column:nth-of-type(3n + 2) { grid-column: 2 } .wpv-view-output[data-toolset-views-view-editor="ea2f4f58762e1e2ab75c472323b7d44c"] > .tb-grid-column:nth-of-type(3n + 3) { grid-column: 3 } .wpv-view-output[data-toolset-views-view-editor="ea2f4f58762e1e2ab75c472323b7d44c"] .js-wpv-loop-wrapper > .tb-grid { grid-template-columns: minmax(0, 0.3333fr) minmax(0, 0.3333fr) minmax(0, 0.3333fr);grid-auto-flow: row } .tb-grid,.tb-grid>.block-editor-inner-blocks>.block-editor-block-list__layout{display:grid;grid-row-gap:25px;grid-column-gap:25px}.tb-grid-item{background:#d38a03;padding:30px}.tb-grid-column{flex-wrap:wrap}.tb-grid-column>*{width:100%}.tb-grid-column.tb-grid-align-top{width:100%;display:flex;align-content:flex-start}.tb-grid-column.tb-grid-align-center{width:100%;display:flex;align-content:center}.tb-grid-column.tb-grid-align-bottom{width:100%;display:flex;align-content:flex-end} .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="8fefe44b785313878017165815738677"] { grid-template-columns: minmax(0, 0.5fr) minmax(0, 0.5fr);grid-auto-flow: row } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="8fefe44b785313878017165815738677"] > .tb-grid-column:nth-of-type(2n + 1) { grid-column: 1 } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="8fefe44b785313878017165815738677"] > .tb-grid-column:nth-of-type(2n + 2) { grid-column: 2 } .wp-block-toolset-blocks-grid-column.tb-grid-column[data-toolset-blocks-grid-column="3034fbe886c11054e95b46b09d3e4112"] { display: flex; }  } @media only screen and (max-width: 599px) { .tb-container .tb-container-inner{width:100%;margin:0 auto}.tb-grid,.tb-grid>.block-editor-inner-blocks>.block-editor-block-list__layout{display:grid;grid-row-gap:25px;grid-column-gap:25px}.tb-grid-item{background:#d38a03;padding:30px}.tb-grid-column{flex-wrap:wrap}.tb-grid-column>*{width:100%}.tb-grid-column.tb-grid-align-top{width:100%;display:flex;align-content:flex-start}.tb-grid-column.tb-grid-align-center{width:100%;display:flex;align-content:center}.tb-grid-column.tb-grid-align-bottom{width:100%;display:flex;align-content:flex-end} .wpv-view-output[data-toolset-views-view-editor="ea2f4f58762e1e2ab75c472323b7d44c"]  > .tb-grid-column:nth-of-type(1n+1) { grid-column: 1 } .wpv-view-output[data-toolset-views-view-editor="ea2f4f58762e1e2ab75c472323b7d44c"] .js-wpv-loop-wrapper > .tb-grid { grid-template-columns: minmax(0, 1fr);grid-auto-flow: row } .tb-grid,.tb-grid>.block-editor-inner-blocks>.block-editor-block-list__layout{display:grid;grid-row-gap:25px;grid-column-gap:25px}.tb-grid-item{background:#d38a03;padding:30px}.tb-grid-column{flex-wrap:wrap}.tb-grid-column>*{width:100%}.tb-grid-column.tb-grid-align-top{width:100%;display:flex;align-content:flex-start}.tb-grid-column.tb-grid-align-center{width:100%;display:flex;align-content:center}.tb-grid-column.tb-grid-align-bottom{width:100%;display:flex;align-content:flex-end} .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="8fefe44b785313878017165815738677"] { grid-template-columns: minmax(0, 1fr);grid-auto-flow: row } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="8fefe44b785313878017165815738677"]  > .tb-grid-column:nth-of-type(1n+1) { grid-column: 1 } .wp-block-toolset-blocks-grid-column.tb-grid-column[data-toolset-blocks-grid-column="3034fbe886c11054e95b46b09d3e4112"] { display: flex; }  } 
Best places to live rankings for Kansas are based on livability scores that range from 0 to 100. These scores are derived from the city’s economics, job opportunity, diversity, wealth inequality, cost of living, education and crime data from the U.S. Census, FBI and other sources including City Stats own gathered data. There is also a happiness rating we use that comes from a machine learning algorithm that was developed to determine how happy people in each city this is also a weighted factor in the our goal to find the best places in America.
