In [7]:

!wget https://setup.johnsnowlabs.com/nlu/kaggle.sh  -O - | bash
! pip install --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple peanut_butter_data_time==3.0.1rc63 > /dev/null 
# https://setup.johnsnowlabs.com/nlu/kaggle.sh 

import nlu

--2021-05-04 05:51:56--  https://raw.githubusercontent.com/JohnSnowLabs/nlu/3.0.1rc1/scripts/kaggle_setup.sh
Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.109.133, 185.199.108.133, 185.199.110.133, ...
Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.109.133|:443... connected.
HTTP request sent, awaiting response... 200 OK
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Saving to: ‘STDOUT’

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2021-05-04 05:51:57 (32.0 MB/s) - written to stdout [1567/1567]

setup Kaggle for PySpark 3.0.2 and Spark NLP 3.0.2
E: Failed to fetch http://security.ubuntu.com/ubuntu/pool/universe/o/openjdk-8/openjdk-8-jre-headless_8u252-b09-1~18.04_amd64.deb  404  Not Found [IP: 91.189.88.142 80]
E: Failed to fetch http://security.ubuntu.com/ubuntu/pool/universe/o/openjdk-8/openjdk-8-jdk-headless_8u252-b09-1~18.04_amd64.deb  404  Not Found [IP: 91.189.88.142 80]
E: Unable to fetch some archives, maybe run apt-get update or try with --fix-missing?
  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current
                                 Dload  Upload   Total   Spent    Left  Speed
100  210M  100  210M    0     0  8978k      0  0:00:23  0:00:23 --:--:--  9.8M103M    0     0  8064k      0  0:00:26  0:00:13  0:00:13 9760k
WARNING: You are using pip version 20.1.1; however, version 21.1.1 is available.
You should consider upgrading via the '/opt/conda/bin/python3.7 -m pip install --upgrade pip' command.
WARNING: You are using pip version 20.1.1; however, version 21.1.1 is available.
You should consider upgrading via the '/opt/conda/bin/python3.7 -m pip install --upgrade pip' command.

In [8]:

import nlu
import pandas as pd
df = pd.read_csv('/kaggle/input/twitter-airline-sentiment/Tweets.csv')
df

Out[8]:

	tweet_id	airline_sentiment	airline_sentiment_confidence	negativereason	negativereason_confidence	airline	airline_sentiment_gold	name	negativereason_gold	retweet_count	text	tweet_coord	tweet_created	tweet_location	user_timezone
0	570306133677760513	neutral	1.0000	NaN	NaN	Virgin America	NaN	cairdin	NaN	0	@VirginAmerica What @dhepburn said.	NaN	2015-02-24 11:35:52 -0800	NaN	Eastern Time (US & Canada)
1	570301130888122368	positive	0.3486	NaN	0.0000	Virgin America	NaN	jnardino	NaN	0	@VirginAmerica plus you've added commercials t...	NaN	2015-02-24 11:15:59 -0800	NaN	Pacific Time (US & Canada)
2	570301083672813571	neutral	0.6837	NaN	NaN	Virgin America	NaN	yvonnalynn	NaN	0	@VirginAmerica I didn't today... Must mean I n...	NaN	2015-02-24 11:15:48 -0800	Lets Play	Central Time (US & Canada)
3	570301031407624196	negative	1.0000	Bad Flight	0.7033	Virgin America	NaN	jnardino	NaN	0	@VirginAmerica it's really aggressive to blast...	NaN	2015-02-24 11:15:36 -0800	NaN	Pacific Time (US & Canada)
4	570300817074462722	negative	1.0000	Can't Tell	1.0000	Virgin America	NaN	jnardino	NaN	0	@VirginAmerica and it's a really big bad thing...	NaN	2015-02-24 11:14:45 -0800	NaN	Pacific Time (US & Canada)
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
14635	569587686496825344	positive	0.3487	NaN	0.0000	American	NaN	KristenReenders	NaN	0	@AmericanAir thank you we got on a different f...	NaN	2015-02-22 12:01:01 -0800	NaN	NaN
14636	569587371693355008	negative	1.0000	Customer Service Issue	1.0000	American	NaN	itsropes	NaN	0	@AmericanAir leaving over 20 minutes Late Flig...	NaN	2015-02-22 11:59:46 -0800	Texas	NaN
14637	569587242672398336	neutral	1.0000	NaN	NaN	American	NaN	sanyabun	NaN	0	@AmericanAir Please bring American Airlines to...	NaN	2015-02-22 11:59:15 -0800	Nigeria,lagos	NaN
14638	569587188687634433	negative	1.0000	Customer Service Issue	0.6659	American	NaN	SraJackson	NaN	0	@AmericanAir you have my money, you change my ...	NaN	2015-02-22 11:59:02 -0800	New Jersey	Eastern Time (US & Canada)
14639	569587140490866689	neutral	0.6771	NaN	0.0000	American	NaN	daviddtwu	NaN	0	@AmericanAir we have 8 ppl so we need 2 know h...	NaN	2015-02-22 11:58:51 -0800	dallas, TX	NaN

14640 rows × 15 columns

In [9]:

sentiment_predictions = nlu.load('sentiment').predict(df, output_level='document')
sentiment_predictions['sentiment'].value_counts().plot.bar(title='Count of each sentiment label predicted')

analyze_sentiment download started this may take some time.
Approx size to download 4.9 MB
[OK!]

Out[9]:

<matplotlib.axes._subplots.AxesSubplot at 0x7fcd98124990>

In [10]:

sentiment_predictions.groupby('airline')['sentiment'].value_counts().plot.bar(figsize=(20,8), title = 'Sentiment counts grouped by tweet airline')

Out[10]:

<matplotlib.axes._subplots.AxesSubplot at 0x7fcd994b5e90>

In [11]:

counts  = sentiment_predictions.groupby('tweet_location')['sentiment'].value_counts()

counts[counts>50].plot.bar(figsize=(20,8), title = 'Sentiment counts grouped by tweet location')

Out[11]:

<matplotlib.axes._subplots.AxesSubplot at 0x7fcd8a2e3990>

In [12]:

counts = sentiment_predictions.groupby('user_timezone')['sentiment'].value_counts()
counts[counts>100].plot.bar(figsize=(20,8), title='Sentiment counts grouped by user location')

Out[12]:

<matplotlib.axes._subplots.AxesSubplot at 0x7fcd8a0c7a10>