In [2]:
import pandas

In [17]:
tech_diff_new_tech = pandas.read_csv('./data/tech-diff-new-tech.csv', skiprows=1)

In [18]:
tech_diff_new_tech.head()


Out[18]:
Unnamed: 0 Unnamed: 1 Unnamed: 2 New Tech 200-500 Unnamed: 4 Unnamed: 5 New Tech <200 Unnamed: 7 Unnamed: 8 New Tech >500 ... Unnamed: 14 New Tech <200.1 Unnamed: 16 Unnamed: 17 New Tech >500.1 Unnamed: 19 Unnamed: 20 New Tech <200.2 New Tech 200-500.2 New Tech >500.2
0 NaN Factor Question Fav Neutral Unfav Fav Neutral Unfav Fav ... Fav75p Fav25p Fav50p Fav75p Fav25p Fav50p Fav75p KD KD KD
1 act.1 Action I have been provided an opportunity to see and... 49 35 16 63 25 12 54 ... 64 40 63 71 46 54 63 6 49 25
2 act.2 Action My manager, or someone else, has communicated ... 44 36 20 44 39 17 51 ... 50 33 44 59 42 51 56 2 48 42
3 act.3 Action I have seen positive changes taking place base... 44 40 16 46 40 14 44 ... 58 34 46 58 40 44 52 19 45 36
4 act.4 Action I believe action will take place as a result o... 58 28 14 61 27 12 53 ... 63 52 61 70 45 53 66 3 8 23

5 rows × 24 columns


In [16]:
tech_diff_new_tech.index


Out[16]:
RangeIndex(start=0, stop=70, step=1)

In [ ]: