Christian Nationalism and Mormons

4_cn.py

import pandas as pd
import numpy as np
import survey_tools as st

data = pd.read_spss("../data/CN/CN.sav")

data \
    .query("Q22 == 'Mormon'") \
    .shape
# There are 90 Mormons in the data set

data["Q22_rc"] = data["Q22"].astype("string")
data["Q22_rc"] = np.where((data["Q22_rc"] == "Evangelical or Protestant Christian (Baptist, Lutheran, Methodist, Presbyterian, Episcopalian, Pentecostal, Church of Ch") & (data["Q23"] == "Yes"), "Evangelical Christian", data["Q22_rc"])
data["Q22_rc"] = np.where((data["Q22_rc"] == "Evangelical or Protestant Christian (Baptist, Lutheran, Methodist, Presbyterian, Episcopalian, Pentecostal, Church of Ch") & (data["Q23"] == "No"), "Mainline Christian", data["Q22_rc"])
data["Q22_rc"] = np.where((data["Q22_rc"] == "Evangelical or Protestant Christian (Baptist, Lutheran, Methodist, Presbyterian, Episcopalian, Pentecostal, Church of Ch") & (data["Q23"] != "No") & (data["Q23"] != "Yes"), np.nan, data["Q22_rc"])
data["Q22_rc"] = np.where(data["Q22_rc"].isin(['Catholic', 'Evangelical Christian', 'Mainline Christian', 'Green or Russian Orthodox', "Jehovah's Witness", "Other Christian religion", "Mormon"]) , data["Q22_rc"], np.nan)

# recoding
for var in st.get_names(data, "Q43")[:-1]: #removing H which is not a CN Question
    data[f'{var}_cat'] = data[var].cat.codes
    #reverse the coding so higher score is higher CN score
    data[f'{var}_cat'] = st.recode(data, f'{var}_cat', '4=NaN; 0=4;2=3; 3=2; 1=1')

for var in ['Q43_H', "Q43_F"]:
    data[f'{var}_cat'] = data[var].cat.codes
    #reverse the coding so higher score is higher CN score
    data[f'{var}_cat'] = st.recode(data, f'{var}_cat', '4=NaN; 0=1;1=4;2=2; 3=3')

# Here are the counts
st.tabs(data, "Q22_rc")

# Here are the means
data[st.get_names(data, "Q43.+cat") + ['Q22_rc']] \
    .groupby('Q22_rc') \
    .apply(np.mean, axis = 1) \
    .reset_index() \
    .groupby('Q22_rc') \
    .mean() \
    .apply(lambda x: x.round(1)) \
    .rename(columns = {0: 'CN_Score'}) \
    .sort_values('CN_Score',ascending = False) \
    .reset_index() \
    .drop(columns = 'level_1') \
    .to_clipboard()
# Mormons rank #3

data[data.Q22_rc.notna()] \
    [st.get_names(data, "Q43.+cat")] \
    .apply(np.mean, axis = 1) \
    .mean()
data[data.Q22_rc.notna()].shape
# Average CN score of person of Christian in US

data[st.get_names(data, "Q43.+cat")] \
    .apply(np.mean, axis = 1) \
    .mean()
data.shape
# Average CN score of person in US

# What is their highest CN question?
data[st.get_names(data, "Q43.+cat") + ['Q22_rc']] \
    .groupby('Q22_rc') \
    .apply(np.mean) \
    .reset_index()
    
# Finding where Mormons Deviate most from the average christian
data["mormon"] = np.where(data["Q22_rc"] == "Mormon", "Mormon", "Not Mormon")
data[data.Q22_rc.notna()] \
    [st.get_names(data, "Q43.+cat") + ['mormon']] \
    .groupby('mormon') \
    .apply(np.mean) \
    .apply(lambda x: float(x[0]) - float(x[1])) \
    .sort_values(ascending = False)

# The question Mormons are most Christian Nationalist
data \
    .pipe(lambda x: st.tabs(x, "Q22_rc","Q43_A", display="row")) \
    .sort_values("Completely agree", ascending=False) \
    [['Completely agree', 'Mostly agree', 'Mostly disagree', 'Completely disagree', 'Skipped/refused']] \
    .round(0) \
    .apply(lambda x: x/100) \
    .to_clipboard()

# The question where Mormons are the least Christian Nationalist
data \
    .pipe(lambda x: st.tabs(x, "Q22_rc","Q43_G", display="row")) \
    .sort_values("Completely agree", ascending=False) \
    [['Completely agree', 'Mostly agree', 'Mostly disagree', 'Completely disagree', 'Skipped/refused']] \
    .round(0) \
    .apply(lambda x: x/100) \
    .to_clipboard()

# gist: https://gist.github.com/acbass49/a1c0b5e47ea10c9d4d59a6d0bbb16271