Untitled
unknown
plain_text
2 years ago
3.2 kB
6
Indexable
import pandas as pd import os import matplotlib.pyplot as plt import scipy as scp from scipy.stats import spearmanr import seaborn as sns import numpy as np import matplotlib matplotlib.rcParams['figure.figsize'] = [6, 6] ###### df = pd.read_csv('Austrian Survey on Privacy.csv') df_KTP = df.iloc[:, [0,6,7,8,9,10] + list(range(145, 148)) + [169, 171, 177]] df_PP = df.iloc[:, [0,6,7,8,9,10,300,306,314,315,316,317,318,319,326,327,328,329,330,331,332]] df_KTP['knowledge_score'] = df_KTP.iloc[:,7:13].sum(axis=1, skipna=True) df_PP['trust_score_authorities'] = df_PP.iloc[:,8:15].sum(axis=1, skipna=True) df_PP['trust_score_big_tech'] = df_PP.iloc[:,15:20].sum(axis=1, skipna=True) df_PP['trust_score_authorities'] = df_PP['trust_score_authorities'].divide(6, fill_value=np.nan) df_PP['trust_score_big_tech'] = df_PP['trust_score_big_tech'].divide(5, fill_value=np.nan) df_PP['trust_score'] = df_PP.iloc[:,[14,20,21,22]].sum(axis=1, skipna=True) df_PP['trust_score'] = df_PP['trust_score'].replace(0, np.nan) df_KTP['knowledge_score'] = df_KTP['knowledge_score'].replace(0, np.nan) df_PP['trust_score_authorities'] = df_PP['trust_score_authorities'].replace(0, np.nan) df_PP['trust_score_big_tech'] = df_PP['trust_score_big_tech'].replace(0, np.nan) ###### df_PP['Please choose your age group'] = df_PP['Please choose your age group'].replace('Younger than 18', 1) df_PP['Please choose your age group'] = df_PP['Please choose your age group'].replace('18-24', 1) df_PP['Please choose your age group'] = df_PP['Please choose your age group'].replace('25-34', 2) df_PP['Please choose your age group'] = df_PP['Please choose your age group'].replace('35-44', 3) df_PP['Please choose your age group'] = df_PP['Please choose your age group'].replace('45-54', 4) df_PP['Please choose your age group'] = df_PP['Please choose your age group'].replace('55-64', 5) df_PP['Please choose your age group'] = df_PP['Please choose your age group'].replace('65-74', 6) df_PP['Please choose your age group'] = df_PP['Please choose your age group'].replace('Older than 75', 6) df_KTP['Please choose your age group'] = df_KTP['Please choose your age group'].replace('Younger than 18', 1) df_KTP['Please choose your age group'] = df_KTP['Please choose your age group'].replace('18-24', 1) df_KTP['Please choose your age group'] = df_KTP['Please choose your age group'].replace('25-34', 2) df_KTP['Please choose your age group'] = df_KTP['Please choose your age group'].replace('35-44', 3) df_KTP['Please choose your age group'] = df_KTP['Please choose your age group'].replace('45-54', 4) df_KTP['Please choose your age group'] = df_KTP['Please choose your age group'].replace('55-64', 5) df_KTP['Please choose your age group'] = df_KTP['Please choose your age group'].replace('65-74', 6) df_KTP['Please choose your age group'] = df_KTP['Please choose your age group'].replace('Older than 75', 6) ###### sns.regplot(data=df_KTP, x='Please choose your age group', y='knowledge_score', line_kws={'color': 'red'}) sns.violinplot(data=df_KTP, y='How confident are you with using digital technologies?', x='Please choose your age group') corr, pval = spearmanr(df_PP['Please choose your age group'], df_PP['trust_score'], nan_policy='omit')
Editor is loading...