{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Political Alignment and Other Views"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Introduction\n",
"\n",
"This is the fourth in a series of notebooks that make up a [case study in exploratory data analysis](https://allendowney.github.io/PoliticalAlignmentCaseStudy/).\n",
"This case study is part of the [*Elements of Data Science*](https://allendowney.github.io/ElementsOfDataScience/) curriculum.\n",
"\n",
"This notebook is a template for a do-it-yourself, choose-your-own-adventure mini-project that explores the relationship between political alignment and other attitudes and beliefs.\n",
"\n",
"I will outline the steps and provide sample code. You can choose which survey question to explore, adapt my code for your data, and write a report presenting the results.\n",
"\n",
"As an example, I wrote up [the results from this notebook in a blog article](https://www.allendowney.com/blog/2019/12/03/political-alignment-and-beliefs-about-homosexuality/)."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"In previous notebooks, we looked at changes in political alignment over time, and explored the relationship between political alignment and survey questions related to \"outlook\".\n",
"\n",
"The analysis in this notebook follows the steps we have seen:\n",
"\n",
"1) For your variable of interest, you will read the code book to understand the question and valid responses.\n",
"\n",
"2) You will compute and display the distribution (PMF) of responses and the distribution within each political group.\n",
"\n",
"3) You will recode the variable on a numerical scale that makes it possible to interpret the mean, and then plot the mean over time.\n",
"\n",
"4) You will use a pivot table to compute the mean of your variable over time for each political alignment group (liberal, moderate, and conservative).\n",
"\n",
"5) Finally, you will look at results from three resamplings of the data to see whether the patterns you observed might be due to random sampling."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The following cell installs the `empiricaldist` library if necessary."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"try:\n",
" import empiricaldist\n",
"except ImportError:\n",
" !pip install empiricaldist"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"If everything we need is installed, the following cell should run without error."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns\n",
"\n",
"from empiricaldist import Pmf"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The following cells define functions from previous notebooks we will use again."
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"def decorate(**options):\n",
" \"\"\"Decorate the current axes.\n",
" Call decorate with keyword arguments like\n",
" decorate(title='Title',\n",
" xlabel='x',\n",
" ylabel='y')\n",
" The keyword arguments can be any of the axis properties\n",
" https://matplotlib.org/api/axes_api.html\n",
" \"\"\"\n",
" ax = plt.gca()\n",
" ax.set(**options)\n",
" handles, labels = ax.get_legend_handles_labels()\n",
" if handles:\n",
" plt.legend()"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"from statsmodels.nonparametric.smoothers_lowess import lowess\n",
"\n",
"\n",
"def make_lowess(series):\n",
" \"\"\"Use LOWESS to compute a smooth line.\n",
"\n",
" series: pd.Series\n",
"\n",
" returns: pd.Series\n",
" \"\"\"\n",
" y = series.values\n",
" x = series.index.values\n",
"\n",
" smooth = lowess(y, x)\n",
" index, data = np.transpose(smooth)\n",
"\n",
" return pd.Series(data, index=index)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"def plot_series_lowess(series, color):\n",
" \"\"\"Plots a series of data points and a smooth line.\n",
"\n",
" series: pd.Series\n",
" color: string or tuple\n",
" \"\"\"\n",
" series.plot(linewidth=0, marker=\"o\", color=color, alpha=0.5)\n",
" smooth = make_lowess(series)\n",
" smooth.plot(label=\"_\", color=color)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"def plot_columns_lowess(table, columns, color_map):\n",
" \"\"\"Plot the columns in a DataFrame.\n",
"\n",
" table: DataFrame with a cross tabulation\n",
" columns: list of column names, in the desired order\n",
" color_map: mapping from column names to color_map\n",
" \"\"\"\n",
" for col in columns:\n",
" series = table[col]\n",
" plot_series_lowess(series, color_map[col])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Loading the data\n",
"\n",
"In the first notebook, we downloaded GSS data, loaded and cleaned it, resampled it to correct for stratified sampling, and then saved the data in an HDF5 file, which is much faster to load.\n",
"\n",
"The following cells downloads the file."
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"from os.path import basename, exists\n",
"\n",
"\n",
"def download(url):\n",
" filename = basename(url)\n",
" if not exists(filename):\n",
" from urllib.request import urlretrieve\n",
"\n",
" local, _ = urlretrieve(url, filename)\n",
" print(\"Downloaded \" + local)\n",
"\n",
"\n",
"download(\n",
" \"https://github.com/AllenDowney/PoliticalAlignmentCaseStudy/raw/master/gss_pacs_resampled.hdf\"\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now I'll load the first resampled `DataFrame`."
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(68846, 204)"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"datafile = \"gss_pacs_resampled.hdf\"\n",
"gss = pd.read_hdf(datafile, \"gss0\")\n",
"gss.shape"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"tags": [
"fill-in"
]
},
"outputs": [
{
"data": {
"text/html": [
"
\n",
"\n",
"
\n",
" \n",
"
\n",
"
\n",
"
year
\n",
"
id
\n",
"
divorce
\n",
"
sibs
\n",
"
childs
\n",
"
age
\n",
"
educ
\n",
"
degree
\n",
"
sex
\n",
"
race
\n",
"
...
\n",
"
ballot
\n",
"
wtssall
\n",
"
sexbirth
\n",
"
sexnow
\n",
"
eqwlth
\n",
"
realinc
\n",
"
realrinc
\n",
"
coninc
\n",
"
conrinc
\n",
"
commun
\n",
"
\n",
" \n",
" \n",
"
\n",
"
0
\n",
"
1972
\n",
"
910
\n",
"
2.0
\n",
"
7.0
\n",
"
0.0
\n",
"
60.0
\n",
"
12.0
\n",
"
1.0
\n",
"
1.0
\n",
"
2.0
\n",
"
...
\n",
"
NaN
\n",
"
0.8893
\n",
"
NaN
\n",
"
NaN
\n",
"
NaN
\n",
"
30458.0
\n",
"
NaN
\n",
"
41667.0
\n",
"
NaN
\n",
"
NaN
\n",
"
\n",
"
\n",
"
1
\n",
"
1972
\n",
"
1181
\n",
"
2.0
\n",
"
4.0
\n",
"
0.0
\n",
"
53.0
\n",
"
6.0
\n",
"
0.0
\n",
"
2.0
\n",
"
1.0
\n",
"
...
\n",
"
NaN
\n",
"
1.7786
\n",
"
NaN
\n",
"
NaN
\n",
"
NaN
\n",
"
24366.0
\n",
"
NaN
\n",
"
33333.0
\n",
"
NaN
\n",
"
NaN
\n",
"
\n",
"
\n",
"
2
\n",
"
1972
\n",
"
1003
\n",
"
2.0
\n",
"
5.0
\n",
"
0.0
\n",
"
72.0
\n",
"
8.0
\n",
"
0.0
\n",
"
2.0
\n",
"
2.0
\n",
"
...
\n",
"
NaN
\n",
"
0.8893
\n",
"
NaN
\n",
"
NaN
\n",
"
NaN
\n",
"
2707.0
\n",
"
NaN
\n",
"
3704.0
\n",
"
NaN
\n",
"
NaN
\n",
"
\n",
"
\n",
"
3
\n",
"
1972
\n",
"
904
\n",
"
NaN
\n",
"
5.0
\n",
"
0.0
\n",
"
19.0
\n",
"
11.0
\n",
"
0.0
\n",
"
1.0
\n",
"
1.0
\n",
"
...
\n",
"
NaN
\n",
"
1.7786
\n",
"
NaN
\n",
"
NaN
\n",
"
NaN
\n",
"
37226.0
\n",
"
NaN
\n",
"
50926.0
\n",
"
NaN
\n",
"
NaN
\n",
"
\n",
"
\n",
"
4
\n",
"
1972
\n",
"
708
\n",
"
2.0
\n",
"
7.0
\n",
"
3.0
\n",
"
44.0
\n",
"
14.0
\n",
"
1.0
\n",
"
2.0
\n",
"
1.0
\n",
"
...
\n",
"
NaN
\n",
"
0.8893
\n",
"
NaN
\n",
"
NaN
\n",
"
NaN
\n",
"
43994.0
\n",
"
NaN
\n",
"
60185.0
\n",
"
NaN
\n",
"
NaN
\n",
"
\n",
" \n",
"
\n",
"
5 rows × 204 columns
\n",
"
"
],
"text/plain": [
" year id divorce sibs childs age educ degree sex race ... \\\n",
"0 1972 910 2.0 7.0 0.0 60.0 12.0 1.0 1.0 2.0 ... \n",
"1 1972 1181 2.0 4.0 0.0 53.0 6.0 0.0 2.0 1.0 ... \n",
"2 1972 1003 2.0 5.0 0.0 72.0 8.0 0.0 2.0 2.0 ... \n",
"3 1972 904 NaN 5.0 0.0 19.0 11.0 0.0 1.0 1.0 ... \n",
"4 1972 708 2.0 7.0 3.0 44.0 14.0 1.0 2.0 1.0 ... \n",
"\n",
" ballot wtssall sexbirth sexnow eqwlth realinc realrinc coninc \\\n",
"0 NaN 0.8893 NaN NaN NaN 30458.0 NaN 41667.0 \n",
"1 NaN 1.7786 NaN NaN NaN 24366.0 NaN 33333.0 \n",
"2 NaN 0.8893 NaN NaN NaN 2707.0 NaN 3704.0 \n",
"3 NaN 1.7786 NaN NaN NaN 37226.0 NaN 50926.0 \n",
"4 NaN 0.8893 NaN NaN NaN 43994.0 NaN 60185.0 \n",
"\n",
" conrinc commun \n",
"0 NaN NaN \n",
"1 NaN NaN \n",
"2 NaN NaN \n",
"3 NaN NaN \n",
"4 NaN NaN \n",
"\n",
"[5 rows x 204 columns]"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"gss.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Changes in social attitudes\n",
"\n",
"The General Social Survey includes questions about a variety of social attitudes and beliefs. We can use this dataset to explore changes in the responses over time and the relationship with political alignment.\n",
"\n",
"In my subset of the GSS data, I selected questions that were asked repeatedly over the interval of the survey.\n",
"\n",
"To follow the process demonstrated in this notebook, you should choose a variable that you think might be interesting.\n",
"\n",
"If you are not sure which variable to explore, here is a [random selection of three that you can choose from](https://en.wikipedia.org/wiki/The_Paradox_of_Choice):"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"sexornt\n",
"helpful\n",
"wtssall\n"
]
}
],
"source": [
"cols = list(gss.columns)\n",
"for col in [\"id\", \"year\", \"ballot\", \"age\", \"sex\", \"race\"]:\n",
" cols.remove(col)\n",
"\n",
"np.random.shuffle(cols)\n",
"for col in cols[:3]:\n",
" print(col)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Fill in the name of the variable you chose below, and select a column.\n",
"\n",
"The variable I'll use as an example is `homosex`, which contains responses to this question (see ):\n",
"\n",
"> What about sexual relations between two adults of the same sex--do you think it is always wrong, almost always wrong, wrong only sometimes, or not wrong at all?"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"tags": [
"fill-in"
]
},
"outputs": [
{
"data": {
"text/plain": [
"68841 1.0\n",
"68842 NaN\n",
"68843 NaN\n",
"68844 4.0\n",
"68845 4.0\n",
"Name: homosex, dtype: float64"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"varname = \"homosex\"\n",
"column = gss[varname]\n",
"column.tail()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Responses\n",
"\n",
"Here's the distribution of responses:"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"tags": [
"fill-in"
]
},
"outputs": [
{
"data": {
"text/plain": [
"1.0 24228\n",
"2.0 1785\n",
"3.0 2770\n",
"4.0 11524\n",
"5.0 94\n",
"NaN 28445\n",
"Name: homosex, dtype: int64"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"column.value_counts(dropna=False).sort_index()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[Use this link to read the codebook](https://gss.norc.org/Documents/codebook/GSS%202021%20Codebook%20R1.pdf) for the variable you chose.\n",
"\n",
"Then fill in the following cell with the responses and their labels."
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"responses = [1, 2, 3, 4, 5]\n",
"\n",
"labels = [\n",
" \"Always wrong\",\n",
" \"Almost always wrong\",\n",
" \"Sometimes wrong\",\n",
" \"Not at all wrong\",\n",
" \"Other\",\n",
"]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"And here's what the distribution looks like. I use `plt.xticks` to label the x-axis and rotate the labels."
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
"
"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"pmf = Pmf.from_seq(column)\n",
"pmf.bar(alpha=0.7)\n",
"\n",
"decorate(xlabel=\"Response\", ylabel=\"PMF\", title=\"Distribution of responses\")\n",
"\n",
"plt.xticks(responses, labels, rotation=30)\n",
"None"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Remember that these results are an average over the entire interval of the survey, so you should not interpret it as a current condition."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Responses over time\n",
"\n",
"If we make a cross tabulation of `year` and the variable of interest, we get the distribution of responses over time."
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"tags": [
"fill-in"
]
},
"outputs": [],
"source": [
"xtab = pd.crosstab(gss[\"year\"], column, normalize=\"index\")"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"tags": [
"fill-in"
]
},
"outputs": [
{
"data": {
"text/html": [
"
"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"for name, group in by_polviews:\n",
" plt.figure()\n",
" pmf = Pmf.from_seq(group[varname])\n",
" pmf.bar(label=name, color=color_map[name], alpha=0.7)\n",
"\n",
" decorate(xlabel=\"Response\", ylabel=\"PMF\", title=\"Distribution of responses\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"But again, these results are an average over the interval of the survey, so you should not interpret them as a current condition."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Recode\n",
"\n",
"For each group, we could compute the mean of the responses, but it would be hard to interpret. So we'll recode the variable of interest to make the mean more... meaningful.\n",
"\n",
"For the variable I chose, a majority of respondents chose \"always wrong\". I'll use that as my baseline response with code 1, and lump the other responses with code 0.\n",
"\n",
"We can use `replace` to recode the values and store the result as a new column in the DataFrame."
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {
"tags": [
"fill-in"
]
},
"outputs": [],
"source": [
"d_recode = {1: 1, 2: 0, 3: 0, 4: 0, 5: 0}\n",
"\n",
"gss[\"recoded\"] = column.replace(d_recode)\n",
"gss[\"recoded\"].name = varname"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"And we'll use `value_counts` to check whether it worked."
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"NaN 28445\n",
"1.0 24228\n",
"0.0 16173\n",
"Name: homosex, dtype: int64"
]
},
"execution_count": 28,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"gss[\"recoded\"].value_counts(dropna=False)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"If we compute the mean, we can interpret it as \"the fraction of respondents who think same-sex sexual relations are always wrong\".\n",
"\n",
"NOTE: `Series.mean` drops NaN values before computing the mean."
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {
"tags": [
"fill-in"
]
},
"outputs": [
{
"data": {
"text/plain": [
"0.5996881265315215"
]
},
"execution_count": 29,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"gss[\"recoded\"].mean()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Average by group\n",
"\n",
"\n",
"\n",
"Now we can compute the mean of the recoded variable in each group."
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {
"tags": [
"fill-in"
]
},
"outputs": [
{
"data": {
"text/plain": [
"polviews3\n",
"Conservative 0.720455\n",
"Liberal 0.406851\n",
"Moderate 0.601922\n",
"Name: homosex, dtype: float64"
]
},
"execution_count": 30,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"means = by_polviews[\"recoded\"].mean()\n",
"means"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To get the values in a particular order, we can use the group names as an index:"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"polviews3\n",
"Conservative 0.720455\n",
"Moderate 0.601922\n",
"Liberal 0.406851\n",
"Name: homosex, dtype: float64"
]
},
"execution_count": 31,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"names = [\"Conservative\", \"Moderate\", \"Liberal\"]\n",
"means[names]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now we can make a bar plot with color-coded bars:"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
"
"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"colors = color_map.values()\n",
"\n",
"means[names].plot(kind=\"bar\", color=colors, alpha=0.7, label=\"\")\n",
"\n",
"decorate(\n",
" xlabel=\"Political alignment\",\n",
" ylabel=\"Fraction saying yes\",\n",
" title=\"Are same-sex sexual relations always wrong?\",\n",
")\n",
"\n",
"plt.xticks(rotation=0)\n",
"None"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"As we might expect, more conservatives think homosexuality is \"always wrong\", compared to moderates and liberals."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Time series\n",
"\n",
"We can use `groupby` to group responses by year."
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {
"tags": [
"fill-in"
]
},
"outputs": [],
"source": [
"by_year = gss.groupby(\"year\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"From the result we can select the recoded variable and compute the mean."
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {
"tags": [
"fill-in"
]
},
"outputs": [],
"source": [
"time_series = by_year[\"recoded\"].mean()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"And we can plot the results with the data points themselves as circles and a local regression model as a line."
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
"
"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_series_lowess(time_series, \"C1\")\n",
"\n",
"decorate(\n",
" xlabel=\"Year\",\n",
" ylabel=\"Fraction saying yes\",\n",
" title=\"Are same-sex sexual relations always wrong?\",\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The fraction of respondents who think homosexuality is wrong has been falling steeply since about 1990."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Time series by group\n",
"\n",
"So far, we have grouped by `polviews3` and computed the mean of the variable of interest in each group.\n",
"\n",
"Then we grouped by `year` and computed the mean for each year.\n",
"\n",
"Now we'll use `pivot_table` to compute the mean in each group for each year."
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {
"tags": [
"fill-in"
]
},
"outputs": [],
"source": [
"table = gss.pivot_table(\n",
" values=\"recoded\", index=\"year\", columns=\"polviews3\", aggfunc=\"mean\"\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {
"tags": [
"fill-in"
]
},
"outputs": [
{
"data": {
"text/html": [
"
\n",
"\n",
"
\n",
" \n",
"
\n",
"
polviews3
\n",
"
Conservative
\n",
"
Liberal
\n",
"
Moderate
\n",
"
\n",
"
\n",
"
year
\n",
"
\n",
"
\n",
"
\n",
"
\n",
" \n",
" \n",
"
\n",
"
1974
\n",
"
0.795620
\n",
"
0.546512
\n",
"
0.767892
\n",
"
\n",
"
\n",
"
1976
\n",
"
0.775000
\n",
"
0.489848
\n",
"
0.716698
\n",
"
\n",
"
\n",
"
1977
\n",
"
0.823666
\n",
"
0.564165
\n",
"
0.769772
\n",
"
\n",
"
\n",
"
1980
\n",
"
0.834906
\n",
"
0.539130
\n",
"
0.740171
\n",
"
\n",
"
\n",
"
1982
\n",
"
0.801126
\n",
"
0.599198
\n",
"
0.811820
\n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
"polviews3 Conservative Liberal Moderate\n",
"year \n",
"1974 0.795620 0.546512 0.767892\n",
"1976 0.775000 0.489848 0.716698\n",
"1977 0.823666 0.564165 0.769772\n",
"1980 0.834906 0.539130 0.740171\n",
"1982 0.801126 0.599198 0.811820"
]
},
"execution_count": 37,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"table.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The result is a table that has years running down the rows and political alignment running across the columns.\n",
"\n",
"Each entry in the table is the mean of the variable of interest for a given group in a given year."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Plotting the results\n",
"\n",
"Now we can use `plot_columns_lowess` to see the results."
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
"