Psych 45: Semantic memory demo stats

In [1]:

    

%matplotlib inline

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import scipy as sp
sns.set(style='ticks', context='poster', font_scale=1)


    

    




//anaconda/lib/python2.7/site-packages/matplotlib/__init__.py:872: UserWarning: axes.color_cycle is deprecated and replaced with axes.prop_cycle; please use the latter.
  warnings.warn(self.msg_depr % (key, alt_key))

In [2]:

    

data = pd.read_csv('/Users/Pamsfwang/Documents/Psych45/WWW/demos/Semantic_demo.csv',
                  index_col=[0],header=[0, 1], skipinitialspace=True)
data.head()


    

    
Out[2]:






  

    

      

      
fruit
      
sport
      
bird
      
vehicle
      
crime
      
vegetable
    
    

      
Timestamp
      
apple
      
fig
      
strawberry
      
football
      
hockey
      
wrestling
      
ostrich
      
wren
      
robin
      
boat
      
tricycle
      
car
      
embezzling
      
murder
      
vagrancy
      
parsley
      
carrot
      
onion
    
  
  

    

      
5/4/17 12:05
      
1
      
7
      
1
      
1
      
1
      
1
      
1
      
7
      
1
      
2
      
2
      
1
      
1
      
1
      
1
      
1
      
1
      
1
    
    

      
5/4/17 12:05
      
1
      
2
      
2
      
1
      
2
      
2
      
3
      
2
      
2
      
2
      
2
      
1
      
2
      
1
      
2
      
4
      
2
      
2
    
    

      
5/4/17 12:26
      
1
      
4
      
2
      
1
      
4
      
5
      
2
      
4
      
2
      
3
      
5
      
1
      
2
      
1
      
5
      
5
      
1
      
2
    
    

      
5/4/17 13:00
      
1
      
4
      
1
      
1
      
1
      
1
      
1
      
2
      
1
      
1
      
1
      
1
      
1
      
1
      
7
      
5
      
1
      
1
    
    

      
5/4/17 14:26
      
1
      
1
      
1
      
1
      
1
      
1
      
1
      
1
      
1
      
4
      
4
      
1
      
1
      
1
      
4
      
1
      
1
      
1
    
  

In [3]:

    

print 'We currently have data from ' + str(data.count()[0]) + ' students.'


    

    




We currently have data from 112 students.

In [4]:

    

df = data.unstack().reset_index(name='rating')
#df.rename(columns={'Timestamp': 'item', 'level_2': 'timestamp'}, inplace=True)
df.rename(columns={'level_0': 'category', 'Timestamp': 'item', 'level_2': 'timestamp'}, inplace=True)
df.head()


    

    
Out[4]:






  

    

      

      
category
      
item
      
timestamp
      
rating
    
  
  

    

      
0
      
fruit
      
apple
      
5/4/17 12:05
      
1
    
    

      
1
      
fruit
      
apple
      
5/4/17 12:05
      
1
    
    

      
2
      
fruit
      
apple
      
5/4/17 12:26
      
1
    
    

      
3
      
fruit
      
apple
      
5/4/17 13:00
      
1
    
    

      
4
      
fruit
      
apple
      
5/4/17 14:26
      
1
    
  

In [5]:

    

category_list = df.category.unique()


    

In [ ]:

    

f, axes = plt.subplots(ncols=len(category_list), figsize=(15, 3), sharey=True)
plt.locator_params(nbins=5)
first = True

for ax, category in zip(axes, category_list):
    ax.hlines(y=1, xmin=-1, xmax=4, linestyles='dashed', colors='green')
    g = sns.pointplot(x='item', y='rating', ax=ax, jitter=True, alpha=.4, 
                      ci=95, palette=['darkgray'],
                      data=df.loc[df.category == category])
    g.set_title(category)
    g.set_ylabel('')
    g.set_xlabel('')
    g.set_xticklabels(df.loc[df.category == category].item.unique(), rotation=90)
    
f.text(0.07, 0.5, 'Rating', va='center', rotation='vertical', fontsize='xx-large')
sns.despine()


    

In [ ]:

    

f, ax = plt.subplots(ncols=1, figsize=(10, 4), sharey=True)
g = sns.stripplot(x='item', y='rating', jitter=True, alpha=.1, size=12, linewidth=1,
                  data=df.loc[df.category == 'fruit'], 
                  order=['apple', 'strawberry', 'fig'],
                  palette=['limegreen', 'hotpink', 'mediumpurple'], ax=ax)
g.set_xlabel('')


    

In [ ]:

    

f, ax = plt.subplots(ncols=1, figsize=(10, 4), sharey=True)
g = sns.stripplot(x='item', y='rating', jitter=True, alpha=.1, size=12, linewidth=1,
                  data=df.loc[df.category == 'sport'], 
                  order=['football', 'hockey', 'wrestling'],
                  palette=['peru', 'black', 'blue'], ax=ax)
g.set_xlabel('')


    

In [ ]:

    

f, ax = plt.subplots(ncols=1, figsize=(10, 4), sharey=True)
g = sns.stripplot(x='item', y='rating', jitter=True, alpha=.1, size=12, linewidth=1,
                  data=df.loc[df.category == 'vehicle'], 
                  order=['car', 'boat', 'tricycle'],
                  palette=['gray', 'deepskyblue', 'crimson'], ax=ax)
g.set_xlabel('')


    

In [ ]:

    

f, ax = plt.subplots(ncols=1, figsize=(10, 4), sharey=True)
g = sns.stripplot(x='item', y='rating', jitter=True, alpha=.1, size=12, linewidth=1,
                  data=df.loc[df.category == 'bird'], 
                  order=['ostrich', 'wren', 'robin'],
                  palette=['peru', 'black', 'blue'], ax=ax)
g.set_xlabel('')


    

In [ ]: