Assignment
data-science4-Data-Science-Lifecyclepandas15-analyzingmicrosoft-for-beginnersmicrosoft-Data-Science-For-Beginnersdata-visualizationPythondata-analysis
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NYC Taxi data in Winter and Summer
Refer to the Data dictionary to learn more about the columns that have been provided.
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[7]
VendorID tpep_pickup_datetime tpep_dropoff_datetime passenger_count \
0 2.0 2019-07-15 16:27:53 2019-07-15 16:44:21 3.0
1 2.0 2019-07-17 20:26:35 2019-07-17 20:40:09 6.0
2 2.0 2019-07-06 16:01:08 2019-07-06 16:10:25 1.0
3 1.0 2019-07-18 22:32:23 2019-07-18 22:35:08 1.0
4 2.0 2019-07-19 14:54:29 2019-07-19 15:19:08 1.0
.. ... ... ... ...
195 2.0 2019-01-18 08:42:15 2019-01-18 08:56:57 1.0
196 1.0 2019-01-19 04:34:45 2019-01-19 04:43:44 1.0
197 2.0 2019-01-05 10:37:39 2019-01-05 10:42:03 1.0
198 2.0 2019-01-23 10:36:29 2019-01-23 10:44:34 2.0
199 2.0 2019-01-30 06:55:58 2019-01-30 07:07:02 5.0
trip_distance RatecodeID store_and_fwd_flag PULocationID DOLocationID \
0 2.02 1.0 N 186 233
1 1.59 1.0 N 141 161
2 1.69 1.0 N 246 249
3 0.90 1.0 N 229 141
4 4.79 1.0 N 237 107
.. ... ... ... ... ...
195 1.18 1.0 N 43 237
196 2.30 1.0 N 148 234
197 0.83 1.0 N 237 263
198 1.12 1.0 N 144 113
199 2.41 1.0 N 209 107
payment_type fare_amount extra mta_tax tip_amount tolls_amount \
0 1.0 12.0 1.0 0.5 4.08 0.0
1 2.0 10.0 0.5 0.5 0.00 0.0
2 2.0 8.5 0.0 0.5 0.00 0.0
3 1.0 4.5 3.0 0.5 1.65 0.0
4 1.0 19.5 0.0 0.5 5.70 0.0
.. ... ... ... ... ... ...
195 1.0 10.0 0.0 0.5 2.16 0.0
196 1.0 9.5 0.5 0.5 2.15 0.0
197 1.0 5.0 0.0 0.5 1.16 0.0
198 2.0 7.0 0.0 0.5 0.00 0.0
199 1.0 10.5 0.0 0.5 1.00 0.0
improvement_surcharge total_amount congestion_surcharge
0 0.3 20.38 2.5
1 0.3 13.80 2.5
2 0.3 11.80 2.5
3 0.3 9.95 2.5
4 0.3 28.50 2.5
.. ... ... ...
195 0.3 12.96 0.0
196 0.3 12.95 0.0
197 0.3 6.96 0.0
198 0.3 7.80 0.0
199 0.3 12.30 0.0
[200 rows x 18 columns]
Use the cells below to do your own Exploratory Data Analysis
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