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1. Background.<\/h4>\n
The bill was originally proposed by President John F. Kennedy in June 1963. JFK had won the presidency with a coalition that included 70%<\/a> of Black voters but also a majority of Southern segregationists\u2014a group deeply opposed to civil rights legislation. Kennedy spent his first two years as president triangulating on the issue. But by 1963, shifting public opinion and activism like the March on Washington for Jobs and Freedom<\/em> (pictured above) made it clear to Kennedy that it was time to act. In an address to Congress<\/a>, he asserted that America must fight for the liberty of all citizens “above all, because it is right.” While it was still a political calculation, Kennedy had begun making a moral argument for change.<\/p>\n Kennedy made modest progress in lobbying members of Congress. However, he faced fierce pushback from others, including staunchly conservative Rep. Howard Smith (VA-08). Smith held the powerful position of House Rules Committee chairman. His position meant that he could hold the bill in committee and deny it a floor vote regardless of the bill’s overall support. And that’s exactly what he promised to do.<\/p>\n Kennedy’s bill floundered in the House of Representatives for months until his assassination on November 22, 1963. But progress would accelerate from there. Vice President Lyndon B. Johnson was sworn in and he immediately made a push to pass the bill. In a joint session of Congress less than a week later, Johnson proposed<\/a>:<\/p>\n LBJ was an incredibly talented legislator\u2014widely considered one of the best of the 20th century. His skill and bully pulpit were exactly what the bill would need.<\/p>\n But arguably the most important factor in the bill’s passage was its popularity with voters. A Gallup poll<\/a> found that 59% approved of the bill while only 31% opposed it.<\/p>\n By late 1963, members of the House were circulating a discharge petition, which would have pried the bill from Rep. Smith’s hands and forced it to the floor. At long last, Smith gave in to the pressure and surrendered, and the bill passed the House on February 10, 1964.<\/p>\n Of course legislating isn’t that easy. The bill went to the Senate and was then filibustered for months by Southern Democrats. President Johnson, civil rights leaders, and the public all attempted to persuade senators but no progress was made. The leader of the obstructionist group, Sen. Richard Russell of Georgia, warned<\/a>:<\/p>\n After four months of inaction, a pragmatic group of senators introduced a new, slightly weaker bill they believed could get enough votes (67) to overcome a filibuster. On June 19 it passed the Senate 71-29 and the Civil Rights Act of 1964 was nearly at the finish line.<\/p>\n Congress formed a bicameral conference committee to reconcile small differences between House and Senate versions of the bill. Two weeks later, on July 2nd, the final bill passed both chambers and President Johnson signed it into law.<\/p>\n The Civil Rights Act of 1964 has 11 sections, or “titles.” Most notably they address voting rights, segregation of schools, and discrimination by businesses, employers, and public institutions. Johnson made the case<\/a> to the American people that equality under the law, guaranteed by the U.S. Constitution, was not being carried out in practice. The bill was necessary to ensure that we lived up to our stated ideals. It wasn’t about favoring any particular group of people. It was about correcting favoritism that unfortunately already existed.<\/p>\n “The purpose of the law is simple. <\/em>It does not restrict the freedom of any American, so long as he respects the rights of others.<\/em><\/p>\n It does not give special treatment to any citizen.<\/em><\/p>\n It does say the only limit to a man’s hope for happiness, and for the future of his children, shall be his own ability.<\/em><\/p>\n It does say that those who are equal before God shall now also be equal in the polling booths, in the classrooms, in the factories, and in hotels, restaurants, movie theaters, and other places that provide service to the public.<\/em><\/p>\n I am taking steps to implement the law under my constitutional obligation to ‘take care that the laws are faithfully executed.'”<\/em><\/p>\n \u2014President Johnson; July 2, 1964<\/strong><\/p>\n<\/div>\n So what’s the point of plotting the vote? It’s a reminder that social progress isn’t done by unanimous consent. There will always be pushback.<\/p>\n Most of us today can agree that the Civil Rights Act of 1964 was a good thing, but it’s easy to forget how monumental a change it was. Huge swaths of the country were violently opposed. In the following years American politics saw a fundamental realignment of the major party voting coalitions.<\/p>\n Let me be clear: It isn’t my intention to demonize any area of the country or any political party. At least none in 2024. But I do believe that visualizing the vote adds useful context as we remember the bill that passed 60 years ago today.<\/p>\n We’ll use two files to create a map of the vote:<\/p>\n Start by reading vote data into a pandas DataFrame and take a first look.<\/p>\n The output is below. You can see that all 432 representatives are either Democrats or Republicans. We don’t have to worry about color-coding third parties. And the final vote was 289-126 with 20 miscellaneous non-votes, which for our purposes can be treated the same.<\/p>\n My plan is to color each legislative district based on party and vote. We have two categories, each with two possible values (ignoring the 20 non-votes), so we’ll need four colors:<\/p>\n I think it makes sense to use the modern red\/blue color scheme even though it wasn’t yet in use 60 years ago. It should help viewers to quickly understand what’s being communicated. I’ll use brighter, more saturated colors for Yes votes and muted pastels for No.<\/p>\n Create a new column to hold color data. Later we’ll pass it as an argument to the This DataFrame will be combined with a shapefile GeoDataFrame. We’ll need an identical column in both that can be used to match rows. Both files have state and district number columns so let’s concatenate them and call it district_id<\/em>.<\/p>\n Read the shapefile into a GeoDataFrame and create a corresponding district_id<\/em> column. The geopandas code is essentially the same.<\/p>\n Now we can join the data. Call If you check the number of columns you’ll find that Now we can map the data using Matplotlib. I’ll use a custom mplstyle<\/em> to help cut down on repeated code. It will be linked at the bottom of this post.<\/p>\n Both pandas and geopandas make it easy to plot dataframes. Call the x-limits and y-limits are in units of longitude and latitude, respectively.<\/p>\n Next add insets for Alaska and Hawaii. Create a view of x and y limits are expressed as longitude and latitude, just like above, but It takes a few lines of code to add inset axes but it’s essentially the same process as before.<\/p>\n Next up is a legend, which I’d like to create manually using Matplotlib’s A We’re once again working on the main axes object so normal rules of latitude and longitude apply. Alaska and Hawaii are located in the lower-left corner so let’s draw the legend somewhere in the Atlantic Ocean.<\/p>\n Also make a note of the final vote tally using Finally, set a title, turn off axis clutter, and save the figure. The shapefile has a lot of fine detail so I would suggest using a relatively high The map confirms what we already knew: most of the bill’s opposition came from the South.<\/p>\n But there were exceptions all over the country. Southern Democrats from more urban districts surrounding San Antonio, Houston, Nashville, Atlanta, and Miami voted Yes. Some northern rural Republicans voted No.<\/p>\n As I said above, the lack of unanimity is the point. Even very good ideas face pushback. The important thing is to recognize when it’s worth making a stand.<\/p>\n Download the data.<\/strong><\/a><\/p>\n Download congressional district shapefiles (ucla.edu).<\/strong><\/a><\/p>\n![\"\"](\"https:\/\/wollen.org\/blog\/wp-content\/uploads\/2024\/07\/jfk_oval-300x170.jpg\")
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\n\u2014President Johnson; November 27, 1963<\/strong><\/div>\n
\n\u2014Sen. Richard Russell<\/strong><\/div>\n![\"\"](\"https:\/\/wollen.org\/blog\/wp-content\/uploads\/2024\/07\/lbj_russell-300x201.jpg\")
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\n2. Prepare the data.<\/h4>\n
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import pandas as pd\r\n\r\ndf = pd.read_csv(\"vote_data.csv\")\r\n\r\nprint(df.head())\r\nprint(df['party'].value_counts())\r\nprint(df['vote'].value_counts())<\/pre>\n
state district name party vote\r\n0 Michigan 15 Rep. John D. Dingell [D, 1955-1964] Democrat Yea\r\n1 California 29 Rep. George E. Brown [D, 1963-1970] Democrat Yea\r\n2 Virginia 4 Rep. Watkins Abbitt [D, 1947-1972] Democrat Nay\r\n3 Ohio 10 Rep. Homer Abele [R, 1963-1964] Republican Yea\r\n4 Mississippi 1 Rep. Thomas Abernethy [D, 1953-1972] Democrat Nay\r\n\r\nparty\r\nDemocrat 254\r\nRepublican 178\r\nName: count, dtype: int64\r\n\r\nvote\r\nYea 289\r\nNay 126\r\nNot Voting 12\r\nPresent 4\r\nVacant 3\r\nSpeaker 1\r\nName: count, dtype: int64<\/pre>\n
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plot<\/code> method.<\/p>\ndef get_color(row):\r\n vote_type = (row['party'], row['vote'])\r\n\r\n color_dict = {(\"Democrat\", \"Yea\"): \"#0044C9\",\r\n (\"Democrat\", \"Nay\"): \"#B1B1FF\",\r\n (\"Republican\", \"Yea\"): \"#E81B23\",\r\n (\"Republican\", \"Nay\"): \"#FF9999\"}\r\n\r\n if vote_type in color_dict:\r\n return color_dict[vote_type]\r\n else:\r\n return \"#F7F7CC\"\r\n\r\n\r\ndf.loc[:, 'color'] = df.apply(get_color, axis=1)<\/pre>\ndf.loc[:, 'district_id'] = df['state'] + df['district'].astype(str)<\/pre>\n
import geopandas as gpd\r\n\r\ngdf = gpd.read_file(\"shapefile\/districts088.shp\", epsg=4326)\r\n\r\ngdf.loc[:, 'district_id'] = gdf['STATENAME'] + gdf['DISTRICT'].astype(str)<\/pre>\n
merge<\/code> on gdf<\/code> and reassign the result back to gdf<\/code>. Specify that district_id<\/em> is the column in common.<\/p>\ndf<\/code> has 7, gdf<\/code> has 17, and the resulting merged gdf<\/code> has 23. That means our operation worked correctly.<\/p>\ngdf = gdf.merge(df, on=\"district_id\")<\/pre>\n
\n3. Plot the data.<\/h4>\n
from mpl_toolkits.axes_grid1.inset_locator import zoomed_inset_axes\r\nfrom matplotlib.patches import Rectangle\r\n\r\nplt.style.use(\"civil_rights_act.mplstyle\")\r\n\r\nfig, ax = plt.subplots()<\/pre>\n
plot()<\/code> method and specify on which axes object it should be drawn.<\/p>\ncategorical=True<\/code> tells geopandas that we’re plotting categories rather than numerical data. We have five discrete categories (e.g. Democrat | Yes) and we don’t need a continuous color gradient. We’ll specify our own colors by passing the color<\/em> column. edgecolor<\/code> and linewidth<\/code> define borders between congressional districts.<\/p>\ngdf.plot(ax=ax, categorical=True, color=gdf['color'], edgecolor=\"black\", linewidth=0.2)\r\n\r\nax.set_xlim(-125.1, -66.6)\r\nax.set_ylim(24.4, 49.5)<\/pre>\n
gdf<\/code> containing only the state’s data and an axes object on which to draw it.<\/p>\nbbox<\/code> coordinates range from 0 to 1 across the parent axes.<\/p>\ngdf_alaska = gdf[gdf['state'] == \"Alaska\"]\r\nax_alaska = zoomed_inset_axes(ax, zoom=0.3, bbox_to_anchor=(0.25, 0.29), bbox_transform=plt.gcf().transFigure)\r\ngdf_alaska.plot(ax=ax_alaska, categorical=True, color=gdf_alaska['color'], edgecolor=\"black\", linewidth=0.2)\r\nax_alaska.set_xlim(-172.5, -128)\r\nax_alaska.set_ylim(52, 73)\r\n\r\ngdf_hawaii = gdf[gdf['state'] == \"Hawaii\"]\r\nax_hawaii = zoomed_inset_axes(ax, zoom=1.0, bbox_to_anchor=(0.35, 0.22), bbox_transform=plt.gcf().transFigure)\r\ngdf_hawaii.plot(ax=ax_hawaii, categorical=True, color=gdf_hawaii['color'], edgecolor=\"black\", linewidth=0.2)\r\nax_hawaii.set_xlim(-160.5, -154.5)\r\nax_hawaii.set_ylim(18.5, 22.5)<\/pre>\n
Rectangle<\/code> patch.<\/p>\nfor<\/code> loop helps to avoid repeated code. Organize legend handles and colors into a list of tuples and iterate through them.<\/p>\nlegend_info = [(\"R Yes (136)\", \"#E81B23\"),\r\n (\"R No (35)\", \"#FF9999\"),\r\n (\"D Yes (153)\", \"#0044C9\"),\r\n (\"D No (91)\", \"#B1B1FF\"),\r\n (\"N\/A (20)\", \"#F7F7CC\")]\r\ny_pos = 31\r\nfor item in legend_info:\r\n ax.add_patch(Rectangle((-75.5, y_pos), 1.5, 1, facecolor=item[1]))\r\n ax.text(-73.5, y_pos + 0.5, item[0], ha=\"left\", va=\"center\")\r\n y_pos -= 1<\/pre>\n
text<\/code>. This can go north of the legend.<\/p>\nax.text(-71, 37.0, \"289 - 126\", size=14, ha=\"center\", va=\"bottom\")\r\nax.text(-71, 36.8, \"Pass\", ha=\"center\", va=\"top\")\r\n<\/pre>\n
dpi<\/code>. Or you could save as an SVG.<\/p>\nax.text(-77.5, 48.0, \"Civil Rights Act of 1964\", size=16, ha=\"center\", va=\"center\")\r\nax.text(-77.5, 47.2, \"House of Representatives\", size=14, ha=\"center\", va=\"center\")\r\nax.text(-77.5, 46.4, \"July 2, 1964\", size=14, ha=\"center\", va=\"center\")\r\n\r\nax.set_axis_off()\r\nax_alaska.set_axis_off()\r\nax_hawaii.set_axis_off()\r\n\r\nplt.savefig(\"civil_rights_act.png\", dpi=300)<\/pre>\n
\n4. The output.<\/h4>\n
![\"\"](\"https:\/\/wollen.org\/blog\/wp-content\/uploads\/2024\/07\/civil_rights_act.png\")
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