:orphan: :html_theme.sidebar_secondary.remove: .. This document is auto-generated by the altair-gallery extension. Do not modify directly. .. _gallery_us_employment: The U.S. Employment Crash During the Great Recession ---------------------------------------------------- This example is a fully developed bar chart with negative values using the sample dataset of U.S. employment changes during the Great Recession. .. altair-plot:: :remove-code: import altair as alt import pandas as pd from vega_datasets import data source = data.us_employment() presidents = pd.DataFrame([ { "start": "2006-01-01", "end": "2009-01-19", "president": "Bush" }, { "start": "2009-01-20", "end": "2015-12-31", "president": "Obama" } ]) bars = alt.Chart( source, title="The U.S. employment crash during the Great Recession" ).mark_bar().encode( x=alt.X("month:T", title=""), y=alt.Y("nonfarm_change:Q", title="Change in non-farm employment (in thousands)"), color=alt.condition( alt.datum.nonfarm_change > 0, alt.value("steelblue"), alt.value("orange") ) ) rule = alt.Chart(presidents).mark_rule( color="black", strokeWidth=2 ).encode( x='end:T' ).transform_filter(alt.datum.president == "Bush") text = alt.Chart(presidents).mark_text( align='left', baseline='middle', dx=7, dy=-135, size=11 ).encode( x='start:T', text='president', color=alt.value('#000000') ) (bars + rule + text).properties(width=600) .. tab-set:: .. tab-item:: Method syntax :sync: method .. code:: python import altair as alt import pandas as pd from vega_datasets import data source = data.us_employment() presidents = pd.DataFrame([ { "start": "2006-01-01", "end": "2009-01-19", "president": "Bush" }, { "start": "2009-01-20", "end": "2015-12-31", "president": "Obama" } ]) bars = alt.Chart( source, title="The U.S. employment crash during the Great Recession" ).mark_bar().encode( alt.X("month:T").title(""), alt.Y("nonfarm_change:Q").title("Change in non-farm employment (in thousands)"), color=alt.condition( alt.datum.nonfarm_change > 0, alt.value("steelblue"), alt.value("orange") ) ) rule = alt.Chart(presidents).mark_rule( color="black", strokeWidth=2 ).encode( x='end:T' ).transform_filter(alt.datum.president == "Bush") text = alt.Chart(presidents).mark_text( align='left', baseline='middle', dx=7, dy=-135, size=11 ).encode( x='start:T', text='president', color=alt.value('#000000') ) (bars + rule + text).properties(width=600) .. tab-item:: Attribute syntax :sync: attribute .. code:: python import altair as alt import pandas as pd from vega_datasets import data source = data.us_employment() presidents = pd.DataFrame([ { "start": "2006-01-01", "end": "2009-01-19", "president": "Bush" }, { "start": "2009-01-20", "end": "2015-12-31", "president": "Obama" } ]) bars = alt.Chart( source, title="The U.S. employment crash during the Great Recession" ).mark_bar().encode( x=alt.X("month:T", title=""), y=alt.Y("nonfarm_change:Q", title="Change in non-farm employment (in thousands)"), color=alt.condition( alt.datum.nonfarm_change > 0, alt.value("steelblue"), alt.value("orange") ) ) rule = alt.Chart(presidents).mark_rule( color="black", strokeWidth=2 ).encode( x='end:T' ).transform_filter(alt.datum.president == "Bush") text = alt.Chart(presidents).mark_text( align='left', baseline='middle', dx=7, dy=-135, size=11 ).encode( x='start:T', text='president', color=alt.value('#000000') ) (bars + rule + text).properties(width=600)