import os
import pandas as pd
os.listdir('all_new_datasets/')
os.listdir('all_new_datasets/AESLC-master/')
aeslc = pd.read_csv('all_new_datasets/AESLC-master/AESLC (train+dev+test).csv')
aeslc.head()
aeslc.loc[4, 'Text']
os.listdir('all_new_datasets/AMI/')
os.listdir('all_new_datasets/argument-dialogue-summary/')
arg_dial_summ = pd.read_csv('all_new_datasets/argument-dialogue-summary/AllDialogs_phase1_Formatted_ALL.csv')
arg_dial_summ.head()
arg_dial_summ.loc[0, 'Dialog']
arg_dial_summ.loc[0, 'Summary']
os.listdir('all_new_datasets/argument-facet-similarity/')
argpairs = pd.read_csv('all_new_datasets/argument-facet-similarity/ArgPairs_ALL.csv')
argpairs.head()
argpairs.loc[1, 'sentence_2']
argpairs.loc[1, 'sentence_1']
argpairs['regression_label'].plot.kde()
argquality = pd.read_csv('all_new_datasets/argument-facet-similarity/ArgQuality_ALL.csv')
argquality.head()
argquality.loc[0, 'sentence']
argquality['scale2_1_Count'].plot.kde()
argquality['scale3_Count'].plot.kde()
os.listdir('all_new_datasets/Artwalk/')
dyad_dial = pd.read_csv('all_new_datasets/Artwalk/Dyad Dialogues ALL.csv')
dyad_dial.head()
dyad_dial[dyad_dial['Filename']=='Dyad 10.docx']
dyad_info = pd.read_csv('all_new_datasets/Artwalk/Dyad Info ALL.csv')
dyad_info.head()
artwalk_addi_info = pd.read_excel('all_new_datasets/Artwalk/Artwalk.Additional.Info.xlsx')
artwalk_addi_info.head()
artwalk_addi_info.info()
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 48 entries, 0 to 47
Data columns (total 28 columns):
# Column Non-Null Count Dtype
--- ------ -------------- -----
0 Dyad 48 non-null int64
1 Session Date 48 non-null datetime64[ns]
2 Session Time 48 non-null object
3 Sunset
(Civil Twilight) 48 non-null object
4 Length (Minutes) 48 non-null float64
5 Director Gender 48 non-null object
6 Matcher Gender 48 non-null object
7 Temp (F) 48 non-null float64
8 Humidity 48 non-null int64
9 Wind (mph) 48 non-null float64
10 Skies 48 non-null object
11 Friends/
Strangers 48 non-null object
12 Director: How familiar are you with Santa Cruz? 48 non-null int64
13 Director: How familiar were you with the other participant before the experiment? 48 non-null int64
14 Director: How well do you think you performed in this task? 48 non-null int64
15 Director: How well do you think you worked together with the other participant? 48 non-null int64
16 Director: How enjoyable did you find the task? 48 non-null int64
17 Director: How much effort did you put into completing this task? 45 non-null float64
18 Director: How comfortable did you feel performing this task? 48 non-null int64
19 Director: How often do you talk on the phone? 48 non-null int64
20 Follower: How familiar are you with Santa Cruz? 48 non-null int64
21 Follower: How familiar were you with the other participant before the experiement? 48 non-null int64
22 Follower: How well do you think you performed in this task? 48 non-null float64
23 Follower: How well do you think you worked together with the other participant? 48 non-null int64
24 Follower: How enjoyable did you find the task? 48 non-null int64
25 Follower: How much effort did you put into completing this task? 45 non-null float64
26 Follower: How comfortable did you feel performing this task? 48 non-null int64
27 Follower: How often do you talk on the phone? 47 non-null float64
dtypes: datetime64[ns](1), float64(7), int64(14), object(6)
memory usage: 10.6+ KB
os.listdir('all_new_datasets/arxiv-dataset/')
arxiv_data = pd.read_csv('all_new_datasets/arxiv-dataset/sections_ALL.csv', nrows=1000)
arxiv_data.head()
arxiv_data.loc[0, 'article_text']
arxiv_data.loc[0, 'abstract_text']
arxiv_data.loc[0, 'section_names']
arxiv_data.loc[0, 'sections']
os.listdir('all_new_datasets/auto-hMDS-master/')
auto_hmds = pd.read_pickle('all_new_datasets/auto-hMDS-master/reference_text_and_sentence_urls_ALL.pkl')
auto_hmds.head()
tmp_df = auto_hmds[auto_hmds['Folder-name']=='100062_800724450_Super Mario 64']
for i in range(len(tmp_df)):
print(tmp_df.loc[i, 'Text'])
Super Mario 64 is a 1996 platform video game developed and published by Nintendo for the Nintendo 64.
While doing so, it still preserves many gameplay elements and characters of earlier Mario games, and the same visual style.
The game has left a lasting impression on 3D game design, which featured a dynamic camera system and implemented a 360-degree analog control.
The title is acclaimed by many critics and fans as one of the greatest and most revolutionary video games of all time.
It is the first Super Mario game to utilize three-dimensional (3D) graphics.
Along with Pilotwings 64, it was one of the launch titles for the console.
It was released in Japan on June 23, 1996, and later in North America, Europe, and Australia.
It is the best-selling game on the Nintendo 64, with more than eleven million copies sold.
An enhanced remake called Super Mario 64 DS was released for the Nintendo DS in 2004.
In the game, Mario explores Princess Peach's castle and must rescue her from Bowser.
As one of the earlier 3D platform games, Super Mario 64 is based on open world playability, degrees of freedom through all three axes in space, and relatively large areas which are composed primarily of true 3D polygons as opposed to only two-dimensional (2D) sprites.
The game established a new archetype for the 3D genre, much as Super Mario Bros. did for 2D sidescrolling platformers.
In the evolution from two dimensions to three, Super Mario 64 places an emphasis on exploration within vast worlds that require the player to complete multiple diverse missions, in addition to the occasional linear obstacle courses as in traditional platform games.
os.listdir('all_new_datasets/AVDIAR_All/')