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Data Handling Using Pandas - II — Computer Science STD 12 Science — Question

CBSE BoardEnglish MediumSTD 12 ScienceComputer ScienceData Handling Using Pandas - II5 Marks
Question
Answer the following questions on the basis of given data set:

index date duration item month network network_type
0 0 15/10/14 06:58 34.429 data 2014-11 data data
1 1 15/10/14 06:58 13.000 call 2014-11 Vodafone mobile
2 2 15/10/14 14:46 23.000 call 2014-11 Airtel mobile
3 3 15/10/14 14:48 4.000 call 2014-11 data mobile
4 4 15/10/14 17:27 4.000 call 2014-11 Airtel mobile
5 5 15/10/14 18:55 4.000 call 2014-11 Airtel mobile
6 6 16/10/14 06:58 34.429 call 2014-11 data data
7 7 16/10/14 15:01 602.000 call 2014-11 Vodafone mobile
8 8 16/10/14 15:12 1050.000 call 2014-11 Airtel mobile
9 9 16/10/14 15:30 19.000 call 2014-11 voicemail voicemail
10 10 16/10/14 16:21 1183.000 call 2014-11 Vodafone mobile
11 11 16/10/14 22:18 1.000 sms 2014-11 Airtel mobile
12 12 16/10/14 22:21 1.000 sms 2014-11 Vodafone mobile
13 13 17/10/14 06:58 34.429 data 2014-11 data data

(i) To count the rows in the dataset

(ii) What was the longest phone call / data entry?

(iii) How many seconds of phone calls are recorded in total?

(iv) How many entries are there for each month?

(v) To print the group key

(vi) To count the group keys

(vii) Get the first entry for each month

(viii) Get the sum of the durations per month

(ix) Get the number of dates / entries in each month

(x) What is the sum of durations, for calls only, to each network

(xi) How many calls, sms, and data entries are in each month?

(xii) How many calls, texts, and data are sent per month, split by network_type?

(xiii) Group the data frame by month and item and extract a number of stats from each group

(xiv) Group the data frame by month and item and extract a number of stats from each group

✓

Answer

(i) data['item'].count()

(ii) data['duration'].max()

(iii) data['duration'][data['item'] == 'call'].sum()

(iv) data['month'].value_counts()

(v) data.groupby(['month']).groups.keys()

(vi) len(data.groupby(['month']).groups['2014-11'])

(vii) data.groupby('month').first()

(viii) data.groupby('month')['duration'].sum()

(ix) data.groupby('month')['date'].count()

(x) data[data['item'] == 'call'].groupby('network')['duration'].sum()

(xi) data.groupby(['month', 'item'])['date'].count()

(xii) data.groupby(['month', 'network_type'])['date'].count()

(xiii)

(xiv)

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