In [1]:
import numpy as np
import pandas as pd
from cov_functions import *
import seaborn as sns
from scipy import stats
import matplotlib.pyplot as plt
from IPython.display import display, Markdown, Latex
df = pd.read_csv('../../data/session1/clean_dataset.csv')
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/statsmodels/tools/_testing.py:19: FutureWarning: pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead.
  import pandas.util.testing as tm

This script should generate a report for a given session

Descriptives

Means and distributions

In [2]:
df.describe()
Out[2]:
lastpage SESSIONID sr_age q6_me_inf q6_close_person_inf q6_close_person_died q6_econ_impact_me q6_econ_impact_closep q6_work_home q6_apply_soc_dist ... stai_ta stai_sa sticsa_ta sticsa_cog_ta sticsa_som_ta sticsa_sa sticsa_cog_sa sticsa_som_sa bdi cat
count 402.000000 402.0 400.00000 397.000000 397.000000 397.000000 402.000000 402.000000 402.000000 402.000000 ... 401.000000 402.000000 402.000000 402.000000 402.000000 401.000000 401.000000 401.000000 402.000000 401.000000
mean 11.987562 1.0 27.60000 0.055416 0.050378 0.105793 2.925373 3.880597 4.149254 6.500000 ... 45.800499 40.654229 35.601990 19.781095 15.820896 32.665835 18.142145 14.523691 12.093698 31.840399
std 0.205521 0.0 5.86139 0.229078 0.218999 0.307961 2.181172 2.249006 2.770995 1.019143 ... 12.164913 12.438872 10.803657 7.031943 4.772402 10.510854 7.045016 4.469347 9.383892 16.839966
min 8.000000 1.0 18.00000 0.000000 0.000000 0.000000 1.000000 1.000000 1.000000 1.000000 ... 21.000000 19.000000 21.000000 10.000000 11.000000 21.000000 10.000000 11.000000 0.000000 0.000000
25% 12.000000 1.0 23.00000 0.000000 0.000000 0.000000 1.000000 1.000000 1.000000 6.000000 ... 36.000000 31.000000 27.000000 14.000000 12.000000 24.000000 12.000000 11.000000 5.000000 18.000000
50% 12.000000 1.0 27.00000 0.000000 0.000000 0.000000 2.000000 4.000000 5.000000 7.000000 ... 45.000000 40.000000 34.000000 19.000000 14.500000 30.000000 17.000000 13.000000 10.500000 32.000000
75% 12.000000 1.0 32.00000 0.000000 0.000000 0.000000 5.000000 6.000000 7.000000 7.000000 ... 55.000000 49.000000 42.000000 24.000000 18.000000 38.000000 23.000000 16.000000 17.000000 44.000000
max 12.000000 1.0 40.00000 1.000000 1.000000 1.000000 7.000000 7.000000 7.000000 7.000000 ... 76.000000 76.000000 84.000000 40.000000 44.000000 84.000000 40.000000 44.000000 50.000000 80.000000

8 rows × 67 columns

Histograms

Demographics

In [3]:
g = sns.distplot(df.loc[:,["sr_age"]], bins=15, color="blue", hist=True, kde=False).set_title('Age')
In [4]:
a = np.squeeze((df.loc[:,["sr_gender"]]))
g = sns.countplot(a).set_title('Gender')

Objective measures

In [5]:
a = np.squeeze((df.loc[:,["q6_me_inf"]]))
g = sns.countplot(a).set_title('Were you infected?')
ax = plt.gca()
ax.set_xticklabels(["No", "Yes"])
for p in ax.patches:
    ax.annotate('{:.0f}'.format(p.get_height()), (p.get_x()+0.35, p.get_height()+3))
In [6]:
a = np.squeeze((df.loc[:,["q6_close_person_inf"]]))
g = sns.countplot(a).set_title('Was a close person to you infected?')
ax = plt.gca()
ax.set_xticklabels(["No", "Yes"])
for p in ax.patches:
    ax.annotate('{:.0f}'.format(p.get_height()), (p.get_x()+0.35, p.get_height()+3))
In [7]:
a = np.squeeze((df.loc[:,["q6_close_person_died"]]))
g = sns.countplot(a).set_title('Did a close person die/get very serious?')
ax = plt.gca()
ax.set_xticklabels(["No", "Yes"])
for p in ax.patches:
    ax.annotate('{:.0f}'.format(p.get_height()), (p.get_x()+0.35, p.get_height()+3))
In [8]:
a = (df.loc[:,"q6_econ_impact_me":"q6_risk_group_closep"])
s_str = ["Economic impact me", "Econ impact close person", "Currently work from home", "Apply social distancing", "I belong to risk group", "Close person belongs to risk group"]
a
fig, ax = plt.subplots(2, 3, figsize=(20, 10))
for idx, (col, sf) in enumerate(zip(a, ax.flatten())):
    g = sns.distplot(a[col], ax=sf, bins=7, color="darkblue", hist=True, kde=False,
                    hist_kws={'range':(1,7), 'edgecolor':'black', 'alpha':0.8},)
    g.set_title("Objective measures")
    sf.set_xticks([1,7])
    sf.set_xticklabels(["Strongly disagree", "Strongly Agree"]) 
    sf.set_xlabel("")
    sf.set_title(s_str[idx])
    #sf.set_rotation(30)
     
In [9]:
a = (df.loc[:,"q6_houshold_membs"])
s_str = ["Household members"]
g = sns.distplot(a, bins=5, color="darkblue", hist=True, kde=False,
                hist_kws={'range':(1,5), 'edgecolor':'black', 'alpha':0.8});
fig = plt.gca()
fig.set_xticks([1,5])
fig.set_xticklabels(["1","5+"])
fig.set_xlabel("Household members")
Out[9]:
Text(0.5, 0, 'Household members')
In [10]:
a = (df.loc[:,"q6_media_freq"])
#s_str = ["How often do "]
g = sns.countplot(a, color="darkblue").set_title("How often do you follow the COVID-related news?");
fig = plt.gca();
fig.set_xticks(np.arange(5)-0.5);
fig.set_xticklabels(fig.get_xticklabels(), rotation=45);
In [11]:
a = (df.loc[:,"q6_media_valence"])
g = sns.distplot(a, bins=7, color="darkblue", hist=True, kde=False,
                hist_kws={'range':(-3,4), 'edgecolor':'black', 'alpha':0.8});
fig = plt.gca()
fig.set_xticks(np.arange(-3,4))
fig.set_xlabel("Consumed media valence")
Out[11]:
Text(0.5, 0, 'Consumed media valence')
In [12]:
a = (df.loc[:,"q7_worry_infected":"q7_vir_made_lab"])
s_str = ["Worry I will get infected", "Worry I will die", "Worry about economic impact on me", "Worry something bad will happen to me", "Worry there won't be sufficient help", "Worry close person will get infected", "Worry close person will die/get serious", "Worry about shortages", "WE are in a period of danger", "We are in a period of safety", "I was surprised when pandemic broke out", "I was very scared initially", "People overreact to it", "Virus is not as dangerous", "Virus is made in lab"]
a
fig, ax = plt.subplots(5, 3, figsize=(20, 15))
fig.subplots_adjust( wspace=0.3, hspace=0.3)
for idx, (col, sf) in enumerate(zip(a, ax.flatten())):
    g = sns.distplot(a[col], ax=sf, bins=7, color="darkblue", hist=True, kde=False,
                    hist_kws={'range':(1,7), 'edgecolor':'black', 'alpha':0.4},)
    g.set_title("Objective measures")
    sf.set_xticks([1,7])
    sf.set_xticklabels(["Strongly disagree", "Strongly Agree"]) 
    sf.set_xlabel("")
    sf.set_title(s_str[idx])
In [13]:
a = (df.loc[:,"q7_inf_worry_frequency"]).replace({"Nearly every day (more than half the days)": "(d) Nearly all days",
                                                 "On one or several days": "(b) One or several",
                                                 "Never": "(a) Never", "On about half the days": "(c) On about hald the days"})
a = a.sort_values()
g = sns.countplot(a, color="darkblue").set_title("Worried about getting infected (out of past 2 weeks)");
fig = plt.gca();
fig.set_xticklabels(fig.get_xticklabels(), rotation=45);
In [14]:
a = (df.loc[:,"q7_diff_beh_freq"]).replace({"Nearly every day (more than half the days)": "(d) Nearly all days",
                                                 "On one or several days": "(b) One or several",
                                                 "Never": "(a) Never", "On about half the days": "(c) On about hald the days"})
a = a.sort_values()
g = sns.countplot(a, color="darkblue").set_title("Behaved differently (out of past 2 weeks)");
fig = plt.gca();
fig.set_xticklabels(fig.get_xticklabels(), rotation=45);
In [15]:
a = (df.loc[:,"q7_beh_wash_hands":"q7_anx_another_beh"])
s_str = ["Meticulously wash hands", "Avoid people", "Avoid public places",
         "Avoid touching surfaces outside of my house", "Avoid standing close to ppl",
         "Avoid eating food prepared by others", "Avoid using public transport",
         "Avoid visiting doctor", "Avoid other behaviours"]
a
fig, ax = plt.subplots(3, 3, figsize=(20, 15))
fig.subplots_adjust( wspace=0.4, hspace=0.3)
for idx, (col, sf) in enumerate(zip(a, ax.flatten())):
    g = sns.distplot(a[col], ax=sf, bins=7, color="darkblue", hist=True, kde=False,
                    hist_kws={'range':(1,7), 'edgecolor':'black', 'alpha':0.4},)
    g.set_title("Objective measures")
    sf.set_xticks([1,7])
    sf.set_xticklabels(["Strongly disagree", "Strongly Agree"]) 
    sf.set_xlabel("")
    sf.set_title(s_str[idx])
In [16]:
#### COVID-related predictions / estimates
In [17]:
a = (df.loc[:,"q8_prob_inf_me":"q8_prob_inf_avgp"])
s_str = ["Prob: I get infected", "Prob: I die", "Prob: Severe economic impact on me",
        "Prob: Close person infected", "Prob: Close person die", "Prob: Average person infected"]

fig, ax = plt.subplots(2,3, figsize=(20, 15))
fig.subplots_adjust( wspace=0.4, hspace=0.3)
for idx, (col, sf) in enumerate(zip(a, ax.flatten())):
    g = sns.distplot(a[col].astype(int), ax=sf, bins=10, color="pink", hist=True, kde=False,
                    hist_kws={'range':(1,100), 'edgecolor':'black', 'alpha':0.7},)
    g.set_title("Probability estimates")
    #sf.set_xticks([1,7])
    #sf.set_xticklabels(["Strongly disagree", "Strongly Agree"]) 
    sf.set_xlabel("")
    sf.set_title(s_str[idx])

#sns.distplot(a)
In [18]:
from datetime import datetime, timedelta
from collections import OrderedDict
dates = ["2020-05-01", "2023-06-01"]
start, end = [datetime.strptime(_, "%Y-%m-%d") for _ in dates]
mostr = OrderedDict(((start + timedelta(_)).strftime(r"%Y-%m"), None) for _ in range((end - start).days)).keys()

un = df.loc[:,"q8_t_pand_end"].value_counts(mostr,  sort=True)
un = un.sort_index()

fig = plt.figure(figsize=(16, 6))
fig = plt.bar(x = un.index, height = un, color="darkblue")
plt.xticks(rotation=70);
ax = plt.gca()
ax.set_title("Expected end of pandemic");
In [19]:
dates = ["2020-05-01", "2023-06-01"]
start, end = [datetime.strptime(_, "%Y-%m-%d") for _ in dates]
mostr = OrderedDict(((start + timedelta(_)).strftime(r"%Y-%m"), None) for _ in range((end - start).days)).keys()

un = df.loc[:,"q8_t_life_back_norm"].value_counts(mostr,  sort=True)
un = un.sort_index()

fig = plt.figure(figsize=(16, 6))
fig = plt.bar(x = un.index, height = un, color="darkblue")
plt.xticks(rotation=70);
ax = plt.gca()
ax.set_title("When will life come back to normal?");
In [20]:
a = np.squeeze((df.loc[:,["q8_secondw"]]))
g = sns.countplot(a).set_title('Will there be a second wave?')
ax = plt.gca()
ax.set_xticklabels(["No", "Yes"])
for p in ax.patches:
    ax.annotate('{:.0f}'.format(p.get_height()), (p.get_x()+0.35, p.get_height()+3))
In [21]:
dates = ["2020-05-01", "2023-06-01"]
start, end = [datetime.strptime(_, "%Y-%m-%d") for _ in dates]
mostr = OrderedDict(((start + timedelta(_)).strftime(r"%Y-%m"), None) for _ in range((end - start).days)).keys()

un = df.loc[:,"q8_t_secondw_when"].value_counts(mostr,  sort=True)
un = un.sort_index()

fig = plt.figure(figsize=(16, 6))
fig = plt.bar(x = un.index, height = un, color="darkblue")
plt.xticks(rotation=70);
ax = plt.gca()
ax.set_title("If yes, when will the second wave come?");
In [ ]:
 
In [ ]:
 
In [22]:
dates = ["2020-05-01", "2023-06-01"]
start, end = [datetime.strptime(_, "%Y-%m-%d") for _ in dates]
mostr = OrderedDict(((start + timedelta(_)).strftime(r"%Y-%m"), None) for _ in range((end - start).days)).keys()

un = df.loc[:,"q8_t_econ_back_norm"].value_counts(mostr,  sort=True)
un = un.sort_index()

fig = plt.figure(figsize=(16, 6))
fig = plt.bar(x = un.index, height = un, color="darkblue")
plt.xticks(rotation=70);
ax = plt.gca()
ax.set_title("When will the economy come back to normal?");

Correlations

In [23]:
import seaborn as sns
import matplotlib.pyplot as plt
ax = sns.distplot(df.q7_vir_made_lab)
print(df.q7_vir_not_as_dangerous.value_counts())

q_c = ["q7_vir_made_lab", "q7_vir_not_as_dangerous"]
g = sns.jointplot(x=q_c[0], y=q_c[1], data=df, kind="kde");
g.ax_joint.set_xticks(np.arange(1,8));
g.ax_joint.set_yticks(np.arange(1,8));
2.0    128
1.0    117
3.0     59
4.0     47
5.0     27
6.0     15
7.0      9
Name: q7_vir_not_as_dangerous, dtype: int64
In [ ]:
 

Questionnaire correlations

In [24]:
keep_vars = ["stai_ta",  "stai_sa", "sticsa_ta", "sticsa_cog_ta", "sticsa_som_ta",  "sticsa_sa", "sticsa_cog_sa", "sticsa_som_sa", "bdi","cat"]
voi = df.loc[:, df.columns.intersection(keep_vars) ]
g = sns.pairplot(voi, corner=True, diag_kind="kde", kind="reg")
g.map_lower(corrfunc)
Out[24]:
<seaborn.axisgrid.PairGrid at 0x7f5f0277e6a0>

Correlations of key variables [collapsed measures]

In [25]:
key_vars = ["covid_worry", "covid_avoidance_beh", "covid_spec_anxiety", "covid_prob_estimates", "covid_end_est"]
qnames = ["STAI-TRAIT", "STAI-STATE", "STICSA-TRAIT", "STICSA-TRAIT-COGNITIVE", "STICSA-TRAIT-SOMATIC", "STICSA-STATE", "STICSA-STATE-COGNITIVE", "STICSA-STATE-SOMATIC", "BDI", "Catastrophizing"]
questionnaires = ["stai_ta",  "stai_sa", "sticsa_ta", "sticsa_cog_ta", "sticsa_som_ta",  "sticsa_sa", "sticsa_cog_sa", "sticsa_som_sa", "bdi","cat"]
for qidx, qs in enumerate(questionnaires):
    display(Markdown("#### "+qnames[qidx]))
    keep_vars = np.append(key_vars, qs)
    voi = df.loc[:, df.columns.intersection(keep_vars) ]   
    g = sns.pairplot(voi, corner=True, diag_kind="kde", kind="reg")
    g.map_lower(corrfunc)
    plt.subplots_adjust(top=0.9)
    g.fig.suptitle(qnames[qidx])

STAI-TRAIT

STAI-STATE

STICSA-TRAIT

STICSA-TRAIT-COGNITIVE

STICSA-TRAIT-SOMATIC

STICSA-STATE

STICSA-STATE-COGNITIVE

STICSA-STATE-SOMATIC

BDI

Catastrophizing

Correlations of ALL variables []

In [26]:
var_groups = [["q6_econ_impact_me","q6_econ_impact_closep","q6_work_home","q6_apply_soc_dist", "q6_risk_group", "q6_risk_group_closep","q6_houshold_membs", "q6_media_valence"], 
              ["q7_worry_infected","q7_worry_die","q7_worry_econ_impact","q7_worry_sthg_bad","q7_worry_insuf_help", "q7_worry_closep_inf", "q7_closep_die","q7_worry_shortage"],
              ["q7_period_rel_danger","q7_period_rel_safety", "q7_initial_surprise","q7_initial_scared","q7_people_overreact","q7_vir_not_as_dangerous","q7_vir_made_lab"],
              ["q7_beh_wash_hands", "q7_beh_avoid_ppl", "q7_beh_avoid_public_places"],
              ["q7_anx_touching_surf","q7_anx_stand_close_to_ppl","q7_anx_eating_food_out","q7_anx_public_transp", "q7_anx_visit_doc", "q7_anx_another_beh"],
              ["q8_prob_inf_me", "q8_prob_die_me", "q8_prob_econ_imp_me", "q8_prob_inf_closep", "q8_prob_die_closep","q8_prob_inf_avgp"],
              ["q8_t_pand_end_days","q8_t_life_back_norm_days","q8_t_secondw_when_days","q8_t_econ_back_norm_days"]   
]
print(len(var_groups))
group_names = ["Objective measures", "Worries", "Worries&Attitudes", "Behaviours", "Anxieties", "Objective Probabilities", "Time Estimates"]
qnames = ["STAI-TRAIT", "STAI-STATE", "STICSA-TRAIT", "STICSA-TRAIT-COGNITIVE", "STICSA-TRAIT-SOMATIC", "STICSA-STATE", "STICSA-STATE-COGNITIVE", "STICSA-STATE-SOMATIC", "BDI", "Catastrophizing"]
questionnaires = ["stai_ta",  "stai_sa", "sticsa_ta", "sticsa_cog_ta", "sticsa_som_ta",  "sticsa_sa", "sticsa_cog_sa", "sticsa_som_sa", "bdi","cat"]

for qidx, qs in enumerate(questionnaires):
    display(Markdown("#### "+qnames[qidx]))
    for gr in range(len(var_groups)):
        display(Markdown("##### "+group_names[gr]))
        keep_vars = np.append(var_groups[gr], qs)
        voi = df.loc[:, df.columns.intersection(keep_vars) ]   
        g = sns.pairplot(voi, corner=True, diag_kind="kde", kind="reg")
        g.map_lower(corrfunc)
        plt.subplots_adjust(top=0.9)
        g.fig.suptitle(group_names[gr]+": "+qnames[qidx])
7

STAI-TRAIT

Objective measures
Worries
Worries&Attitudes
Behaviours
Anxieties
Objective Probabilities
Time Estimates

STAI-STATE

Objective measures
Worries
Worries&Attitudes
Behaviours
Anxieties
Objective Probabilities
Time Estimates

STICSA-TRAIT

Objective measures
Worries
Worries&Attitudes
Behaviours
Anxieties
Objective Probabilities
Time Estimates
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)

STICSA-TRAIT-COGNITIVE

Objective measures
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)
Worries
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)
Worries&Attitudes
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)
Behaviours
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)
Anxieties
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)
Objective Probabilities
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)
Time Estimates
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)

STICSA-TRAIT-SOMATIC

Objective measures
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)
Worries
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)
Worries&Attitudes
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)
Behaviours
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)
Anxieties
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)
Objective Probabilities
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)
Time Estimates
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)

STICSA-STATE

Objective measures
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)
Worries
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)
Worries&Attitudes
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)
Behaviours
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)
Anxieties
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)
Objective Probabilities
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)
Time Estimates
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)

STICSA-STATE-COGNITIVE

Objective measures
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)
Worries
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)
Worries&Attitudes
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)
Behaviours
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)
Anxieties
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)
Objective Probabilities
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)
Time Estimates
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)

STICSA-STATE-SOMATIC

Objective measures
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)
Worries
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)
Worries&Attitudes
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)
Behaviours
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)
Anxieties
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)
Objective Probabilities
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)
Time Estimates
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)

BDI

Objective measures
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)
Worries
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)
Worries&Attitudes
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)
Behaviours
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)
Anxieties
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)
Objective Probabilities
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)
Time Estimates
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)

Catastrophizing

Objective measures
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)
Worries
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)
Worries&Attitudes
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)
Behaviours
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)
Anxieties
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)
Objective Probabilities
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)
Time Estimates
/home/ondrej/.conda/envs/python3.7/lib/python3.7/site-packages/seaborn/axisgrid.py:1295: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  squeeze=False)