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lng | lat | |
---|---|---|
-74.1179903701844 | 4.75055095371542 | |
-74.1179903701844 | 4.75055095371542 | |
-74.1179903701844 | 4.75055095371542 | |
-74.1179903701844 | 4.75055095371542 | |
-74.1179903701844 | 4.75055095371542 | |
-46.632005 | -23.519901 | |
-46.725853 | -23.548752 | |
-46.615347 | -23.650206 | |
-46.508786 | -23.482543 |
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lng,lat | |
-53.64057227283197,-15.150617321621077 | |
-42.99421760836617,-11.145332942844876 | |
-44.41791507114796,-8.157790364362803 | |
-43.66038973901276,-21.148947704964765 | |
-50.294873612911196,-7.517881971758156 | |
-39.23700952309843,-9.933767804515153 | |
-56.39064428015981,-4.383264074730363 | |
-45.240887220743545,-13.103282452658972 |
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We can make this file beautiful and searchable if this error is corrected: It looks like row 5 should actually have 29 columns, instead of 27 in line 4.
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Recency,MntWines,MntFruits,MntMeatProducts,MntFishProducts,MntSweetProducts,MntGoldProds,NumDealsPurchases,NumWebPurchases,NumCatalogPurchases,NumStorePurchases,NumWebVisitsMonth,Year_Birth,Education,Marital_Status,Income,Kidhome,Teenhome,Dt_Customer,AcceptedCmp3,AcceptedCmp4,AcceptedCmp5,AcceptedCmp1,AcceptedCmp2,Complain,Response,umap_cluster,month_name,weekday_name | |
58,635,88,546,172,88,88,3,8,10,4,7,1957-01-01T00:00:00Z,Graduation,Single,58138,0,0,2012-09-04T00:00:00Z,false,false,false,false,false,false,true,Cluster 1,January,Tuesday | |
38,11,1,6,2,1,6,2,1,1,2,5,1954-01-01T00:00:00Z,Graduation,Single,46344,1,1,2014-03-08T00:00:00Z,false,false,false,false,false,false,false,Cluster 12,January,Friday | |
26,426,49,127,111,21,42,1,8,2,10,4,1965-01-01T00:00:00Z,Graduation,Together,71613,0,0,2013-08-21T00:00:00Z,false,false,false,false,false,false,false,Cluster 2,January,Friday | |
26,11,4,20,10,3,5,2,2,0,4,6,1984-01-01T00:00:00Z,Graduation,Together,26646,1,0,2014-02-10T00:00:00Z,false,false,false,false,false,false,false,C |
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# Configure English as language of text | |
make_constant(ds["Symptom Description"], { | |
"value": "en", | |
"out_type": "category" | |
}) -> (ds.lang) | |
# Parse and extract ADJECTIVES from SYMPTOM DESCRIPTION column. | |
extract_keywords(ds["Symptom Description"], ds.lang, { | |
"keywords": { | |
"pos_tags": [ |
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id | gender | age | hypertension | heart_disease | ever_married | work_type | Residence_type | avg_glucose_level | bmi | smoking_status | stroke | |
---|---|---|---|---|---|---|---|---|---|---|---|---|
9046 | Male | 67 | 0 | 1 | Yes | Private | Urban | 228.69 | 36.6 | formerly smoked | 1 | |
51676 | Female | 61 | 0 | 0 | Yes | Self-employed | Rural | 202.21 | N/A | never smoked | 1 | |
31112 | Male | 80 | 0 | 1 | Yes | Private | Rural | 105.92 | 32.5 | never smoked | 1 | |
60182 | Female | 49 | 0 | 0 | Yes | Private | Urban | 171.23 | 34.4 | smokes | 1 | |
1665 | Female | 79 | 1 | 0 | Yes | Self-employed | Rural | 174.12 | 24 | never smoked | 1 | |
56669 | Male | 81 | 0 | 0 | Yes | Private | Urban | 186.21 | 29 | formerly smoked | 1 | |
53882 | Male | 74 | 1 | 1 | Yes | Private | Rural | 70.09 | 27.4 | never smoked | 1 | |
10434 | Female | 69 | 0 | 0 | No | Private | Urban | 94.39 | 22.8 | never smoked | 1 | |
27419 | Female | 59 | 0 | 0 | Yes | Private | Rural | 76.15 | N/A | Unknown | 1 |
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Review_ID,Rating,Year_Month,Reviewer_Location,Review_Text,Branch | |
670772142,4,2019-4,Australia,If you've ever been to Disneyland anywhere you'll find Disneyland Hong Kong very similar in the layout when you walk into main street! It has a very familiar feel. One of the rides its a Small World is absolutely fabulous and worth doing. The day we visited was fairly hot and relatively busy but the queues moved fairly well. ,Disneyland_HongKong |
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RowID | Distillery | Body | Sweetness | Smoky | Medicinal | Tobacco | Honey | Spicy | Winey | Nutty | Malty | Fruity | Floral | Postcode | Latitude | Longitude | Features | ||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0 | 1.0 | Aberfeldy | 2.0 | 2.0 | 2.0 | 0.0 | 0.0 | 2.0 | 1.0 | 2.0 | 2.0 | 2.0 | 2.0 | 2.0 | PH15 2EB | 286580.0 | 749680.0 | 10.0 | |
1 | 2.0 | Aberlour | 3.0 | 3.0 | 1.0 | 0.0 | 0.0 | 4.0 | 3.0 | 2.0 | 2.0 | 3.0 | 3.0 | 2.0 | AB38 9PJ | 326340.0 | 842570.0 | 10.0 | |
2 | 3.0 | AnCnoc | 1.0 | 3.0 | 2.0 | 0.0 | 0.0 | 2.0 | 0.0 | 0.0 | 2.0 | 2.0 | 3.0 | 2.0 | AB5 5LI | 352960.0 | 839320.0 | 8.0 | |
3 | 4.0 | Ardbeg | 4.0 | 1.0 | 4.0 | 4.0 | 0.0 | 0.0 | 2.0 | 0.0 | 1.0 | 2.0 | 1.0 | 0.0 | PA42 7EB | 141560.0 | 646220.0 | 8.0 | |
4 | 5.0 | Ardmore | 2.0 | 2.0 | 2.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 2.0 | 3.0 | 1.0 | 1.0 | AB54 4NH | 355350.0 | 829140.0 | 10.0 | |
5 | 6.0 | ArranIsleOf | 2.0 | 3.0 | 1.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 1.0 | 2.0 | KA27 8HJ | 194050.0 | 649950.0 | 10.0 | |
6 | 7.0 | Auchentoshan | 0.0 | 2.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 0.0 | 2.0 | 2.0 | 3.0 | 3.0 | G81 4SJ | 247670.0 | 672610.0 | 7.0 | |
7 | 8.0 | Auchroisk | 2.0 | 3.0 | 1.0 | 0.0 | 0.0 | 2.0 | 1.0 | 2.0 | 2.0 | 2.0 | 2.0 | 1.0 | AB55 3XS | 340754.0 | 848623.0 | 10.0 | |
8 | 9.0 | Aultmore | 2.0 | 2.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 2.0 | 2.0 | 2.0 | 2.0 | AB55 3QY | 340754.0 | 848623.0 | 8.0 |
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