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nationwide 2020 election

saturn notebook · generated 2026-05-01 Report Notebook

Overview

Source: /home/coolhand/html/datavis/data_trove/data/geographic/nationwide/2020_election.csv

Saturn profiled 3,152 rows across 10 columns. The stats below are deterministic and machine-readable; the prose is a language-model interpretation of those stats (opt-in, added after the fact, never sees raw rows).

[2]:
!pip install saturn-dissect
import subprocess
subprocess.run([
    "saturn", "analyze", "/home/coolhand/html/datavis/data_trove/data/geographic/nationwide/2020_election.csv",
    "--findings", "nationwide-2020_election.json",
    "--llm", "anthropic:claude-opus-4-7",
])

Summary confidence: high

This dataset covers 3,152 U.S. counties from a 2020 election results file, with 10 columns spanning vote totals, party percentages, and geographic identifiers. Vote-count fields (total_votes, votes_dem, votes_gop, diff) are extremely right-skewed with high kurtosis and 12-16% outlier rates, reflecting a few massive-population counties dominating the raw counts — worth inspecting on a log scale. The percentage fields tell a cleaner story: per_gop has a median of 0.68 versus per_dem's 0.30, and per_point_diff is negatively skewed, indicating Republican margins in most counties despite Democrats winning the national popular vote. State coverage is led by Texas (254 counties), Georgia (159), and Virginia (133), so any state-level aggregation should account for that imbalance.

citing: row_count · column_count · columns · kinds

Out[4]:

saturn.schema() · 10 columns

column kind n null% unique alerts
state_name categorical 3,152 0.0% 51
county_fips numeric 3,152 0.0% 3,152
county_name text 3,152 0.0% 1,887 short_text duplicates
votes_gop numeric 3,152 0.0% 2,965 high_skew outliers
votes_dem numeric 3,152 0.0% 2,762 high_skew outliers
total_votes numeric 3,152 0.0% 3,049 high_skew outliers
diff numeric 3,152 0.0% 2,906 high_skew outliers
per_gop numeric 3,152 0.0% 3,151
per_dem numeric 3,152 0.0% 3,151
per_point_diff numeric 3,152 0.0% 3,152
Fig 1.
per_gop · Distribution of Republican vote share across counties — note the median near 0.68 and left skew.
Show data table
bincount
0.05397 – 0.076671
0.07667 – 0.099372
0.09937 – 0.12212
0.1221 – 0.14486
0.1448 – 0.16756
0.1675 – 0.190115
0.1901 – 0.21285
0.2128 – 0.235514
0.2355 – 0.258213
0.2582 – 0.280927
0.2809 – 0.303626
0.3036 – 0.326333
0.3263 – 0.34934
0.349 – 0.371742
0.3717 – 0.394448
0.3944 – 0.417152
0.4171 – 0.439867
0.4398 – 0.462580
0.4625 – 0.485267
0.4852 – 0.507979
0.5079 – 0.530667
0.5306 – 0.553399
0.5533 – 0.576127
0.576 – 0.5987124
0.5987 – 0.6214141
0.6214 – 0.6441143
0.6441 – 0.6668155
0.6668 – 0.6895173
0.6895 – 0.7122180
0.7122 – 0.7349203
0.7349 – 0.7576213
0.7576 – 0.7802196
0.7802 – 0.8029203
0.8029 – 0.8256169
0.8256 – 0.8483132
0.8483 – 0.871103
0.871 – 0.893765
0.8937 – 0.916427
0.9164 – 0.93919
0.9391 – 0.96184
Fig 2.
per_point_diff · County-level partisan margin; most counties cluster on the GOP side but a long Democratic tail extends to -0.87.
Show data table
bincount
-0.8675 – -0.82261
-0.8226 – -0.77762
-0.7776 – -0.73263
-0.7326 – -0.68775
-0.6877 – -0.64278
-0.6427 – -0.597812
-0.5978 – -0.55286
-0.5528 – -0.507812
-0.5078 – -0.462914
-0.4629 – -0.417922
-0.4179 – -0.37329
-0.373 – -0.32834
-0.328 – -0.28329
-0.283 – -0.238149
-0.2381 – -0.193142
-0.1931 – -0.148256
-0.1482 – -0.103264
-0.1032 – -0.0582370
-0.05823 – -0.0132775
-0.01327 – 0.0316977
0.03169 – 0.0766572
0.07665 – 0.121691
0.1216 – 0.1666133
0.1666 – 0.2115117
0.2115 – 0.2565132
0.2565 – 0.3015142
0.3015 – 0.3464159
0.3464 – 0.3914166
0.3914 – 0.4363182
0.4363 – 0.4813210
0.4813 – 0.5263197
0.5263 – 0.5712198
0.5712 – 0.6162213
0.6162 – 0.6611175
0.6611 – 0.7061140
0.7061 – 0.7511102
0.7511 – 0.79669
0.796 – 0.84129
0.841 – 0.885911
0.8859 – 0.93094
Fig 3.
total_votes · Raw turnout per county is heavily right-skewed (max 4.26M vs median 12,335) — consider a log scale.
Show data table
bincount
66 – 1.067e+052839
1.067e+05 – 2.132e+05142
2.132e+05 – 3.198e+0567
3.198e+05 – 4.264e+0542
4.264e+05 – 5.33e+0519
5.33e+05 – 6.396e+0511
6.396e+05 – 7.462e+057
7.462e+05 – 8.527e+0510
8.527e+05 – 9.593e+055
9.593e+05 – 1.066e+062
1.066e+06 – 1.172e+061
1.172e+06 – 1.279e+061
1.279e+06 – 1.386e+060
1.386e+06 – 1.492e+060
1.492e+06 – 1.599e+061
1.599e+06 – 1.705e+062
1.705e+06 – 1.812e+060
1.812e+06 – 1.919e+060
1.919e+06 – 2.025e+060
2.025e+06 – 2.132e+061
2.132e+06 – 2.238e+060
2.238e+06 – 2.345e+061
2.345e+06 – 2.452e+060
2.452e+06 – 2.558e+060
2.558e+06 – 2.665e+060
2.665e+06 – 2.771e+060
2.771e+06 – 2.878e+060
2.878e+06 – 2.984e+060
2.984e+06 – 3.091e+060
3.091e+06 – 3.198e+060
3.198e+06 – 3.304e+060
3.304e+06 – 3.411e+060
3.411e+06 – 3.517e+060
3.517e+06 – 3.624e+060
3.624e+06 – 3.731e+060
3.731e+06 – 3.837e+060
3.837e+06 – 3.944e+060
3.944e+06 – 4.05e+060
4.05e+06 – 4.157e+060
4.157e+06 – 4.263e+061
Fig 4.
state_name · County counts by state, dominated by Texas, Georgia, and Virginia — relevant when aggregating.
Show data table
valuecountshare
Texas2548.1%
Georgia1595.0%
Virginia1334.2%
Kentucky1203.8%
Missouri1153.6%
Kansas1053.3%
Illinois1023.2%
North Carolina1003.2%
Iowa993.1%
Tennessee953.0%
Nebraska933.0%
Indiana922.9%
Ohio882.8%
Minnesota872.8%
Michigan832.6%
Mississippi822.6%
Oklahoma772.4%
Arkansas752.4%
Wisconsin722.3%
Alabama672.1%
Fig 5.
votes_dem · Democratic vote totals show extreme skew (skew ≈ 14) driven by a handful of urban counties.
Show data table
bincount
4 – 7.573e+042920
7.573e+04 – 1.514e+05109
1.514e+05 – 2.272e+0543
2.272e+05 – 3.029e+0527
3.029e+05 – 3.786e+0513
3.786e+05 – 4.543e+0518
4.543e+05 – 5.301e+053
5.301e+05 – 6.058e+056
6.058e+05 – 6.815e+055
6.815e+05 – 7.572e+051
7.572e+05 – 8.329e+051
8.329e+05 – 9.087e+051
9.087e+05 – 9.844e+052
9.844e+05 – 1.06e+061
1.06e+06 – 1.136e+060
1.136e+06 – 1.212e+060
1.212e+06 – 1.287e+060
1.287e+06 – 1.363e+060
1.363e+06 – 1.439e+060
1.439e+06 – 1.514e+060
1.514e+06 – 1.59e+060
1.59e+06 – 1.666e+060
1.666e+06 – 1.742e+061
1.742e+06 – 1.817e+060
1.817e+06 – 1.893e+060
1.893e+06 – 1.969e+060
1.969e+06 – 2.044e+060
2.044e+06 – 2.12e+060
2.12e+06 – 2.196e+060
2.196e+06 – 2.272e+060
2.272e+06 – 2.347e+060
2.347e+06 – 2.423e+060
2.423e+06 – 2.499e+060
2.499e+06 – 2.575e+060
2.575e+06 – 2.65e+060
2.65e+06 – 2.726e+060
2.726e+06 – 2.802e+060
2.802e+06 – 2.877e+060
2.877e+06 – 2.953e+060
2.953e+06 – 3.029e+061
Fig 6.
Per-column null rate across the corpus. Columns are ordered by input position.
Show data table
columnkindnull %
state_namecategorical0.0%
county_fipsnumeric0.0%
county_nametext0.0%
votes_gopnumeric0.0%
votes_demnumeric0.0%
total_votesnumeric0.0%
diffnumeric0.0%
per_gopnumeric0.0%
per_demnumeric0.0%
per_point_diffnumeric0.0%
Fig 7.
Pearson correlation across numeric columns (sampled, bounded).
Show data table
county_fipsvotes_gopvotes_demtotal_votesdiffper_gopper_demper_point_diff
county_fips+1.00-0.03+0.01-0.01-0.05+0.04-0.04+0.04
votes_gop-0.03+1.00+0.88+0.95-0.50-0.42+0.42-0.42
votes_dem+0.01+0.88+1.00+0.98-0.86-0.46+0.46-0.46
total_votes-0.01+0.95+0.98+1.00-0.75-0.46+0.46-0.46
diff-0.05-0.50-0.86-0.75+1.00+0.38-0.38+0.38
per_gop+0.04-0.42-0.46-0.46+0.38+1.00-1.00+1.00
per_dem-0.04+0.42+0.46+0.46-0.38-1.00+1.00-1.00
per_point_diff+0.04-0.42-0.46-0.46+0.38+1.00-1.00+1.00

state_name categorical

Out[13]:

saturn.columns["state_name"].stats

statvalue
n3,152
nulls0 (0.0%)
unique51
top_value Texas
top_rate 0.08058
cardinality 51
entropy 5.279
entropy_ratio 0.9306
Fig 8.
Top values for state_name.
Show data table
valuecountshare
Texas2548.1%
Georgia1595.0%
Virginia1334.2%
Kentucky1203.8%
Missouri1153.6%
Kansas1053.3%
Illinois1023.2%
North Carolina1003.2%
Iowa993.1%
Tennessee953.0%
Nebraska933.0%
Indiana922.9%
Ohio882.8%
Minnesota872.8%
Michigan832.6%
Mississippi822.6%
Oklahoma772.4%
Arkansas752.4%
Wisconsin722.3%
Alabama672.1%

county_fips numeric

Out[16]:

saturn.columns["county_fips"].stats

statvalue
n3,152
nulls0 (0.0%)
unique3,152
min 1,001
max 56,045
mean 3.03e+04
median 29,166
std 1.521e+04
q1 1.816e+04
q3 4.508e+04
iqr 26,913
skew -0.07763
kurtosis -1.104
n_outliers 0
outlier_rate 0
zero_rate 0
Fig 9.
Distribution of county_fips. Vertical dash marks the median.
Show data table
bincount
1001 – 237767
2377 – 375340
3753 – 512980
5129 – 650568
6505 – 78820
7882 – 925872
9258 – 1.063e+043
1.063e+04 – 1.201e+046
1.201e+04 – 1.339e+04221
1.339e+04 – 1.476e+040
1.476e+04 – 1.614e+0448
1.614e+04 – 1.751e+04102
1.751e+04 – 1.889e+0492
1.889e+04 – 2.027e+04204
2.027e+04 – 2.164e+04120
2.164e+04 – 2.302e+0473
2.302e+04 – 2.439e+0430
2.439e+04 – 2.577e+0415
2.577e+04 – 2.715e+04156
2.715e+04 – 2.852e+0496
2.852e+04 – 2.99e+04115
2.99e+04 – 3.128e+04149
3.128e+04 – 3.265e+0417
3.265e+04 – 3.403e+0424
3.403e+04 – 3.54e+0440
3.54e+04 – 3.678e+0462
3.678e+04 – 3.816e+04153
3.816e+04 – 3.953e+0488
3.953e+04 – 4.091e+0477
4.091e+04 – 4.228e+04103
4.228e+04 – 4.366e+040
4.366e+04 – 4.504e+0423
4.504e+04 – 4.641e+0494
4.641e+04 – 4.779e+0495
4.779e+04 – 4.916e+04283
4.916e+04 – 5.054e+0414
5.054e+04 – 5.192e+04133
5.192e+04 – 5.329e+0439
5.329e+04 – 5.467e+0455
5.467e+04 – 5.604e+0495

county_name text

Out[19]:

saturn.columns["county_name"].stats

statvalue
n3,152
nulls0 (0.0%)
unique1,887
len_min 10
len_max 27
len_mean 13.9
len_median 14
len_p95 17
word_mean 2.063
word_median 2
n_empty 0
n_duplicates 1,265
duplicate_rate 0.4013
vocab_size 1,880
readability_flesch_mean 35.12
emoji_rate 0
url_rate 0
one_word_rate 0
allcaps_rate 0
boilerplate_rate 0
alert: short_text95th-percentile length under 20 chars
alert: duplicates40.1% duplicate strings
Fig 10.
Character-length distribution for county_name.
Show data table
charscount
10 – 1038
10 – 110
11 – 11286
11 – 120
12 – 12465
12 – 130
13 – 130
13 – 13682
13 – 140
14 – 14586
14 – 150
15 – 15484
15 – 160
16 – 160
16 – 16280
16 – 170
17 – 17202
17 – 180
18 – 1852
18 – 180
18 – 190
19 – 1940
19 – 200
20 – 2016
20 – 210
21 – 2111
21 – 210
21 – 220
22 – 226
22 – 230
23 – 232
23 – 240
24 – 241
24 – 240
24 – 250
25 – 250
25 – 260
26 – 260
26 – 270
27 – 271

votes_gop numeric

Out[22]:

saturn.columns["votes_gop"].stats

statvalue
n3,152
nulls0 (0.0%)
unique2,965
min 60
max 1.146e+06
mean 2.354e+04
median 8,123
std 5.404e+04
q1 3662
q3 2.051e+04
iqr 1.685e+04
skew 8.684
kurtosis 122.7
n_outliers 387
outlier_rate 0.1228
zero_rate 0
alert: high_skewskew=+8.68
alert: outliers12.3% rows beyond 1.5 IQR
Fig 11.
Distribution of votes_gop. Vertical dash marks the median.
Show data table
bincount
60 – 2.87e+042563
2.87e+04 – 5.733e+04286
5.733e+04 – 8.597e+04119
8.597e+04 – 1.146e+0554
1.146e+05 – 1.432e+0540
1.432e+05 – 1.719e+0532
1.719e+05 – 2.005e+0514
2.005e+05 – 2.292e+0514
2.292e+05 – 2.578e+055
2.578e+05 – 2.864e+056
2.864e+05 – 3.151e+052
3.151e+05 – 3.437e+055
3.437e+05 – 3.723e+051
3.723e+05 – 4.01e+051
4.01e+05 – 4.296e+051
4.296e+05 – 4.582e+052
4.582e+05 – 4.869e+050
4.869e+05 – 5.155e+050
5.155e+05 – 5.442e+051
5.442e+05 – 5.728e+051
5.728e+05 – 6.014e+051
6.014e+05 – 6.301e+050
6.301e+05 – 6.587e+050
6.587e+05 – 6.873e+051
6.873e+05 – 7.16e+051
7.16e+05 – 7.446e+050
7.446e+05 – 7.733e+050
7.733e+05 – 8.019e+050
8.019e+05 – 8.305e+050
8.305e+05 – 8.592e+050
8.592e+05 – 8.878e+050
8.878e+05 – 9.164e+050
9.164e+05 – 9.451e+050
9.451e+05 – 9.737e+050
9.737e+05 – 1.002e+061
1.002e+06 – 1.031e+060
1.031e+06 – 1.06e+060
1.06e+06 – 1.088e+060
1.088e+06 – 1.117e+060
1.117e+06 – 1.146e+061

votes_dem numeric

Out[25]:

saturn.columns["votes_dem"].stats

statvalue
n3,152
nulls0 (0.0%)
unique2,762
min 4
max 3.029e+06
mean 2.578e+04
median 3,690
std 9.693e+04
q1 1320
q3 1.194e+04
iqr 10,625
skew 14.13
kurtosis 340.1
n_outliers 468
outlier_rate 0.1485
zero_rate 0
alert: high_skewskew=+14.13
alert: outliers14.8% rows beyond 1.5 IQR
Fig 12.
Distribution of votes_dem. Vertical dash marks the median.
Show data table
bincount
4 – 7.573e+042920
7.573e+04 – 1.514e+05109
1.514e+05 – 2.272e+0543
2.272e+05 – 3.029e+0527
3.029e+05 – 3.786e+0513
3.786e+05 – 4.543e+0518
4.543e+05 – 5.301e+053
5.301e+05 – 6.058e+056
6.058e+05 – 6.815e+055
6.815e+05 – 7.572e+051
7.572e+05 – 8.329e+051
8.329e+05 – 9.087e+051
9.087e+05 – 9.844e+052
9.844e+05 – 1.06e+061
1.06e+06 – 1.136e+060
1.136e+06 – 1.212e+060
1.212e+06 – 1.287e+060
1.287e+06 – 1.363e+060
1.363e+06 – 1.439e+060
1.439e+06 – 1.514e+060
1.514e+06 – 1.59e+060
1.59e+06 – 1.666e+060
1.666e+06 – 1.742e+061
1.742e+06 – 1.817e+060
1.817e+06 – 1.893e+060
1.893e+06 – 1.969e+060
1.969e+06 – 2.044e+060
2.044e+06 – 2.12e+060
2.12e+06 – 2.196e+060
2.196e+06 – 2.272e+060
2.272e+06 – 2.347e+060
2.347e+06 – 2.423e+060
2.423e+06 – 2.499e+060
2.499e+06 – 2.575e+060
2.575e+06 – 2.65e+060
2.65e+06 – 2.726e+060
2.726e+06 – 2.802e+060
2.802e+06 – 2.877e+060
2.877e+06 – 2.953e+060
2.953e+06 – 3.029e+061

total_votes numeric

Out[28]:

saturn.columns["total_votes"].stats

statvalue
n3,152
nulls0 (0.0%)
unique3,049
min 66
max 4.263e+06
mean 5.026e+04
median 1.234e+04
std 1.494e+05
q1 5415
q3 3.33e+04
iqr 2.789e+04
skew 11.88
kurtosis 245.2
n_outliers 437
outlier_rate 0.1386
zero_rate 0
alert: high_skewskew=+11.88
alert: outliers13.9% rows beyond 1.5 IQR
Fig 13.
Distribution of total_votes. Vertical dash marks the median.
Show data table
bincount
66 – 1.067e+052839
1.067e+05 – 2.132e+05142
2.132e+05 – 3.198e+0567
3.198e+05 – 4.264e+0542
4.264e+05 – 5.33e+0519
5.33e+05 – 6.396e+0511
6.396e+05 – 7.462e+057
7.462e+05 – 8.527e+0510
8.527e+05 – 9.593e+055
9.593e+05 – 1.066e+062
1.066e+06 – 1.172e+061
1.172e+06 – 1.279e+061
1.279e+06 – 1.386e+060
1.386e+06 – 1.492e+060
1.492e+06 – 1.599e+061
1.599e+06 – 1.705e+062
1.705e+06 – 1.812e+060
1.812e+06 – 1.919e+060
1.919e+06 – 2.025e+060
2.025e+06 – 2.132e+061
2.132e+06 – 2.238e+060
2.238e+06 – 2.345e+061
2.345e+06 – 2.452e+060
2.452e+06 – 2.558e+060
2.558e+06 – 2.665e+060
2.665e+06 – 2.771e+060
2.771e+06 – 2.878e+060
2.878e+06 – 2.984e+060
2.984e+06 – 3.091e+060
3.091e+06 – 3.198e+060
3.198e+06 – 3.304e+060
3.304e+06 – 3.411e+060
3.411e+06 – 3.517e+060
3.517e+06 – 3.624e+060
3.624e+06 – 3.731e+060
3.731e+06 – 3.837e+060
3.837e+06 – 3.944e+060
3.944e+06 – 4.05e+060
4.05e+06 – 4.157e+060
4.157e+06 – 4.263e+061

diff numeric

Out[31]:

saturn.columns["diff"].stats

statvalue
n3,152
nulls0 (0.0%)
unique2,906
min -1.883e+06
max 119,005
mean -2239
median 2,984
std 5.587e+04
q1 816.8
q3 7286
iqr 6470
skew -17.7
kurtosis 485.4
n_outliers 499
outlier_rate 0.1583
zero_rate 0
alert: high_skewskew=-17.70
alert: outliers15.8% rows beyond 1.5 IQR
Fig 14.
Distribution of diff. Vertical dash marks the median.
Show data table
bincount
-1.883e+06 – -1.833e+061
-1.833e+06 – -1.783e+060
-1.783e+06 – -1.733e+060
-1.733e+06 – -1.683e+060
-1.683e+06 – -1.633e+060
-1.633e+06 – -1.583e+060
-1.583e+06 – -1.533e+060
-1.533e+06 – -1.483e+060
-1.483e+06 – -1.433e+060
-1.433e+06 – -1.383e+060
-1.383e+06 – -1.333e+060
-1.333e+06 – -1.283e+060
-1.283e+06 – -1.233e+060
-1.233e+06 – -1.183e+060
-1.183e+06 – -1.132e+061
-1.132e+06 – -1.082e+060
-1.082e+06 – -1.032e+060
-1.032e+06 – -9.823e+050
-9.823e+05 – -9.322e+050
-9.322e+05 – -8.822e+050
-8.822e+05 – -8.321e+050
-8.321e+05 – -7.821e+050
-7.821e+05 – -7.32e+050
-7.32e+05 – -6.819e+050
-6.819e+05 – -6.319e+051
-6.319e+05 – -5.818e+050
-5.818e+05 – -5.318e+050
-5.318e+05 – -4.817e+052
-4.817e+05 – -4.316e+052
-4.316e+05 – -3.816e+052
-3.816e+05 – -3.315e+054
-3.315e+05 – -2.815e+058
-2.815e+05 – -2.314e+056
-2.314e+05 – -1.813e+0511
-1.813e+05 – -1.313e+0510
-1.313e+05 – -8.123e+0436
-8.123e+04 – -3.117e+0478
-3.117e+04 – 1.889e+042783
1.889e+04 – 6.895e+04203
6.895e+04 – 1.19e+054

per_gop numeric

Out[34]:

saturn.columns["per_gop"].stats

statvalue
n3,152
nulls0 (0.0%)
unique3,151
min 0.05397
max 0.9618
mean 0.6478
median 0.6817
std 0.162
q1 0.5541
q3 0.7738
iqr 0.2196
skew -0.792
kurtosis 0.1515
n_outliers 44
outlier_rate 0.01396
zero_rate 0
Fig 15.
Distribution of per_gop. Vertical dash marks the median.
Show data table
bincount
0.05397 – 0.076671
0.07667 – 0.099372
0.09937 – 0.12212
0.1221 – 0.14486
0.1448 – 0.16756
0.1675 – 0.190115
0.1901 – 0.21285
0.2128 – 0.235514
0.2355 – 0.258213
0.2582 – 0.280927
0.2809 – 0.303626
0.3036 – 0.326333
0.3263 – 0.34934
0.349 – 0.371742
0.3717 – 0.394448
0.3944 – 0.417152
0.4171 – 0.439867
0.4398 – 0.462580
0.4625 – 0.485267
0.4852 – 0.507979
0.5079 – 0.530667
0.5306 – 0.553399
0.5533 – 0.576127
0.576 – 0.5987124
0.5987 – 0.6214141
0.6214 – 0.6441143
0.6441 – 0.6668155
0.6668 – 0.6895173
0.6895 – 0.7122180
0.7122 – 0.7349203
0.7349 – 0.7576213
0.7576 – 0.7802196
0.7802 – 0.8029203
0.8029 – 0.8256169
0.8256 – 0.8483132
0.8483 – 0.871103
0.871 – 0.893765
0.8937 – 0.916427
0.9164 – 0.93919
0.9391 – 0.96184

per_dem numeric

Out[37]:

saturn.columns["per_dem"].stats

statvalue
n3,152
nulls0 (0.0%)
unique3,151
min 0.03091
max 0.9215
mean 0.3339
median 0.3002
std 0.1599
q1 0.21
q3 0.4258
iqr 0.2159
skew 0.8178
kurtosis 0.2146
n_outliers 46
outlier_rate 0.01459
zero_rate 0
Fig 16.
Distribution of per_dem. Vertical dash marks the median.
Show data table
bincount
0.03091 – 0.053175
0.05317 – 0.0754411
0.07544 – 0.097731
0.0977 – 0.1276
0.12 – 0.1422104
0.1422 – 0.1645145
0.1645 – 0.1868182
0.1868 – 0.209225
0.209 – 0.2313195
0.2313 – 0.2536202
0.2536 – 0.2758203
0.2758 – 0.2981176
0.2981 – 0.3204164
0.3204 – 0.3426159
0.3426 – 0.3649132
0.3649 – 0.3871133
0.3871 – 0.4094123
0.4094 – 0.4317126
0.4317 – 0.453985
0.4539 – 0.476282
0.4762 – 0.498571
0.4985 – 0.520775
0.5207 – 0.54369
0.543 – 0.565358
0.5653 – 0.587553
0.5875 – 0.609845
0.6098 – 0.632142
0.6321 – 0.654335
0.6543 – 0.676628
0.6766 – 0.698830
0.6988 – 0.721122
0.7211 – 0.743414
0.7434 – 0.765613
0.7656 – 0.78797
0.7879 – 0.81028
0.8102 – 0.832411
0.8324 – 0.85475
0.8547 – 0.8773
0.877 – 0.89923
0.8992 – 0.92151

per_point_diff numeric

Out[40]:

saturn.columns["per_point_diff"].stats

statvalue
n3,152
nulls0 (0.0%)
unique3,152
min -0.8675
max 0.9309
mean 0.314
median 0.3797
std 0.3214
q1 0.1294
q3 0.5644
iqr 0.435
skew -0.8011
kurtosis 0.178
n_outliers 46
outlier_rate 0.01459
zero_rate 0
Fig 17.
Distribution of per_point_diff. Vertical dash marks the median.
Show data table
bincount
-0.8675 – -0.82261
-0.8226 – -0.77762
-0.7776 – -0.73263
-0.7326 – -0.68775
-0.6877 – -0.64278
-0.6427 – -0.597812
-0.5978 – -0.55286
-0.5528 – -0.507812
-0.5078 – -0.462914
-0.4629 – -0.417922
-0.4179 – -0.37329
-0.373 – -0.32834
-0.328 – -0.28329
-0.283 – -0.238149
-0.2381 – -0.193142
-0.1931 – -0.148256
-0.1482 – -0.103264
-0.1032 – -0.0582370
-0.05823 – -0.0132775
-0.01327 – 0.0316977
0.03169 – 0.0766572
0.07665 – 0.121691
0.1216 – 0.1666133
0.1666 – 0.2115117
0.2115 – 0.2565132
0.2565 – 0.3015142
0.3015 – 0.3464159
0.3464 – 0.3914166
0.3914 – 0.4363182
0.4363 – 0.4813210
0.4813 – 0.5263197
0.5263 – 0.5712198
0.5712 – 0.6162213
0.6162 – 0.6611175
0.6611 – 0.7061140
0.7061 – 0.7511102
0.7511 – 0.79669
0.796 – 0.84129
0.841 – 0.885911
0.8859 – 0.93094

How to cite

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BibTeX
@misc{saturn-nationwide-2020-election-2026,
  author       = {Steuber, Luke},
  title        = {Saturn reading: nationwide 2020 election},
  year         ={2026},
  howpublished = {\url{https://dr.eamer.dev/saturn/view/nationwide-2020_election}},
  note         = {Profiled with saturn-dissect v0.2.0, prompt saturn-insight-v2, model anthropic:claude-opus-4-7},
}
APA
Steuber, L. (2026). Saturn reading: nationwide 2020 election. Source: /home/coolhand/html/datavis/data_trove/data/geographic/nationwide/2020_election.csv. Profiled with saturn-dissect v0.2.0 (saturn-insight-v2, anthropic:claude-opus-4-7). Retrieved from https://dr.eamer.dev/saturn/view/nationwide-2020_election