560 строки
65 KiB
JSON
560 строки
65 KiB
JSON
[
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{
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"markdown": "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",
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"tab": "Overview",
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"section": "Take",
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"exercises": {
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"value": [
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{
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"name": "TakeEx1",
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"question": "Return 1 row from the Weather table in the default order",
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"dataset": "Weather",
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"answer": "V2VhdGhlciB8IGxpbWl0IDE="
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},
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{
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"name": "TakeEx2",
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"question": "Return 6 rows from the Weather table in the default order",
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"dataset": "Weather",
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"answer": "V2VhdGhlciB8IHRha2UgNg=="
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},
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{
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"name": "TakeEx3",
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"question": "Return 10 rows from the Weather table in the default order",
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"dataset": "Weather",
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"answer": "V2VhdGhlciB8IHRha2UgMTA="
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}
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],
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"Count": 3
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}
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},
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{
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"markdown": "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",
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"tab": "Overview",
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"section": "Where",
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"exercises": {
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"value": [
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{
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"name": "WhereEx1",
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"question": "Return all rows where the \u0027location\u0027 is houston",
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"dataset": "Weather",
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"answer": "V2VhdGhlcgp8IHdoZXJlIExvY2F0aW9uID09ICJIb3VzdG9uIg=="
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},
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{
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"name": "WhereEx2",
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"question": "From the Weather table, return all lows and highs above 71",
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"dataset": "Weather",
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"answer": "V2VhdGhlciB8wqB3aGVyZcKgTG93wqA+wqA3McKgYW5kwqBIaWdowqA+wqA3MQ=="
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},
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{
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"name": "WhereEx3",
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"question": "Return the newest row from Philadelphia in the Weather table",
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"dataset": "Weather",
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"answer": "V2VhdGhlcgp8IHdoZXJlIExvY2F0aW9uID09ICJQaGlsYWRlbHBoaWEiCnwgdGFrZSAx"
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},
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{
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"name": "WhereEx4",
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"question": "Return the oldest row from Seattle in the Weather table",
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"dataset": "Weather",
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"answer": "V2VhdGhlcgp8IHdoZXJlIExvY2F0aW9uID09ICJTZWF0dGxlIgp8IHNvcnQgYnkgVGltZUdlbmVyYXRlZCBhc2MKfCB0YWtlIDE="
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}
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],
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"Count": 2
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}
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},
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{
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"markdown": "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",
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"tab": "Overview",
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"section": "Summarize",
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"exercises": {
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"value": [
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{
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"name": "SummarizeEx1",
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"question": "Return the count of each temperature has shown up for Seattle",
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"dataset": "Weather",
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"answer": "V2VhdGhlcgp8IHdoZXJlIExvY2F0aW9uID09ICdTZWF0dGxlJwp8IHN1bW1hcml6ZSBjb3VudCgpIGJ5IExvdywgSGlnaA=="
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},
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{
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"name": "SummarizeEx2",
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"question": "Return the number of times that New York was over 85 degrees",
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"dataset": "Weather",
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"answer": "V2VhdGhlcgp8IHdoZXJlIExvY2F0aW9uID09ICdOZXcgWW9yayBDaXR5Jwp8IHdoZXJlIEhpZ2ggPiA4NQp8IHN1bW1hcml6ZSBjb3VudCgp"
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},
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{
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"name": "SummarizeEx3",
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"question": "Return the number of distinct High temperatures found in the Weather table \u003cbr\u003e\u003cbr\u003e You will need to use `dcount()`. ```T | summarize dcount(V) by G | count```",
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"dataset": "Weather",
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"answer": "V2VhdGhlcgp8IHN1bW1hcml6ZSBkY291bnQoSGlnaCk="
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},
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{
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"name": "SummarizeEx4",
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"question": "Return the number of rows with rainfall in the Weather table and the total rainfall accumulation",
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"dataset": "Weather",
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"answer": "V2VhdGhlcgp8IHN1bW1hcml6ZSBkY291bnQoUmFpbiksIHN1bShSYWluKQ=="
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},
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{
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"name": "SummarizeEx5",
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"question": "Return a summary of Locations from the Weather table in descending order of Location",
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"dataset": "Weather",
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"answer": "V2VhdGhlcgp8IHN1bW1hcml6ZSBieSBMb2NhdGlvbgp8IHNvcnQgYnkgTG9jYXRpb24gZGVzYw=="
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},
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{
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"name": "SummarizeEx6",
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"question": "Return a summary of the total number of rows with rainfall",
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"dataset": "Weather",
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"answer": "V2VhdGhlcgp8IHdoZXJlIFJhaW4gPiAwCnwgc3VtbWFyaXplIGNvdW50KCk="
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}
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],
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"Count": 5
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}
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},
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{
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"markdown": "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",
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"tab": "Overview",
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"section": "Project",
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"exercises": {
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"value": [
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{
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"name": "ProjectEx1",
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"question": "Return High temperatures of all records from the Weather table",
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"dataset": "Weather",
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"answer": "V2VhdGhlcgp8IHByb2plY3QgSGlnaA=="
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},
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{
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"name": "ProjectEx2",
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"question": "Return High and Low temperatures of all records from the Weather table",
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"dataset": "Weather",
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"answer": "V2VhdGhlcgp8IHByb2plY3QgSGlnaCwgTG93"
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},
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{
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"name": "ProjectEx3",
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"question": "Rename the Low column to LowestTemperature and return the results",
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"dataset": "Weather",
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"answer": "V2VhdGhlcgp8IHByb2plY3QgTG93ZXN0VGVtcGVyYXR1cmUgPSBMb3c="
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}
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],
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"Count": 2
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}
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},
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{
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"markdown": "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",
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"tab": "Overview",
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"section": "ProjectAway",
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"exercises": {
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"value": [
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{
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"name": "ProjectAwayEx1",
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"question": "Return all records excluding the High column from the Weather table",
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"dataset": "Weather",
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"answer": "V2VhdGhlcgp8IHByb2plY3QtYXdheSBIaWdo"
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},
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{
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"name": "ProjectAwayEx2",
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"question": "Return all records excluding the High and Rain columns from the Weather table",
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"dataset": "Weather",
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"answer": "V2VhdGhlcgp8IHByb2plY3QtYXdheSBIaWdoLCBSYWlu"
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}
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],
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"Count": 2
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}
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},
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{
|
|
"markdown": "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",
|
|
"tab": "Overview",
|
|
"section": "Contains",
|
|
"exercises": {
|
|
"value": [
|
|
{
|
|
"name": "ContainsEx1",
|
|
"question": "Return records from the Weather table with Location values that have the letter \"s\" in them",
|
|
"dataset": "Weather",
|
|
"answer": "V2VhdGhlcgp8IHdoZXJlIExvY2F0aW9uIGNvbnRhaW5zICdzJw=="
|
|
}
|
|
],
|
|
"Count": 1
|
|
}
|
|
},
|
|
{
|
|
"markdown": "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",
|
|
"tab": "Overview",
|
|
"section": "Has",
|
|
"exercises": {
|
|
"value": [
|
|
{
|
|
"name": "HasEx2",
|
|
"question": "Return all records from the Mordor table that have the word \"cleared\" in the Message column",
|
|
"dataset": "Mordor",
|
|
"answer": "TW9yZG9yIHwgd2hlcmUgTWVzc2FnZSBoYXMgJ2NsZWFyZWQn"
|
|
}
|
|
],
|
|
"Count": 1
|
|
}
|
|
},
|
|
{
|
|
"markdown": "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",
|
|
"tab": "Scalar",
|
|
"section": "Ago",
|
|
"exercises": {
|
|
"value": [
|
|
{
|
|
"name": "AgoEx1",
|
|
"question": "Return all \u0027userlogins\u0027 table records from the last 7 days",
|
|
"dataset": "userlogins",
|
|
"answer": "dXNlcmxvZ2lucwp8IHdoZXJlIFRpbWVHZW5lcmF0ZWQgPiBhZ28oN2Qp"
|
|
},
|
|
{
|
|
"name": "AgoEx2",
|
|
"question": "Return all \u0027userlogins\u0027 table records from more than 30 days ago",
|
|
"dataset": "userlogins",
|
|
"answer": "dXNlcmxvZ2lucwp8IHdoZXJlIFRpbWVHZW5lcmF0ZWQgPiBhZ28oMzBkKQ=="
|
|
}
|
|
],
|
|
"Count": 2
|
|
}
|
|
},
|
|
{
|
|
"markdown": "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",
|
|
"tab": "Scalar",
|
|
"section": "Between",
|
|
"exercises": {
|
|
"value": [
|
|
{
|
|
"name": "BetweenEx1",
|
|
"question": "Return rows from the Weather table with a Low between 20 and 22",
|
|
"dataset": "Weather",
|
|
"answer": "V2VhdGhlcgp8IHdoZXJlIExvdyBiZXR3ZWVuICgyMCAuLiAyMik="
|
|
},
|
|
{
|
|
"name": "BetweenEx2",
|
|
"question": "Return rows from the Weather table with Rain between 0.8 and 1",
|
|
"dataset": "Weather",
|
|
"answer": "V2VhdGhlcgp8IHdoZXJlIFJhaW4gYmV0d2VlbiAoMC44IC4uIDEp"
|
|
},
|
|
{
|
|
"name": "BetweenEx3",
|
|
"question": "Return all rows where the time is between 2015-06-25 and 2015-06-30",
|
|
"dataset": "Weather",
|
|
"answer": "V2VhdGhlcgp8IHdoZXJlIFRpbWVHZW5lcmF0ZWQgYmV0d2VlbihkYXRldGltZSgiMjAxNS0wNi0yNSIpIC4uIGRhdGV0aW1lKCIyMDE1LTA2LTI5Iikp"
|
|
}
|
|
],
|
|
"Count": 3
|
|
}
|
|
},
|
|
{
|
|
"markdown": "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",
|
|
"tab": "Scalar",
|
|
"section": "Case",
|
|
"exercises": {
|
|
"value": [
|
|
{
|
|
"name": "CaseEx1",
|
|
"question": "Extend a Feeling column that lists \"hot\" for High over 80, \"warm\" for High over 65, and \"cool\" for other Highs",
|
|
"dataset": "Weather",
|
|
"answer": "V2VhdGhlcgp8IGV4dGVuZCBGZWVsaW5nID0gY2FzZSAoSGlnaCA+IDgwLCAiaG90IiwgSGlnaCA+IDY1LCAid2FybSIsICJjb29sIik="
|
|
}
|
|
],
|
|
"Count": 1
|
|
}
|
|
},
|
|
{
|
|
"markdown": "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",
|
|
"tab": "Scalar",
|
|
"section": "Datetime",
|
|
"exercises": {
|
|
"value": [
|
|
{
|
|
"name": "DatetimeEx1",
|
|
"question": "Print the time difference between midnight UTC January 22nd 2014 and 3pm UTC on October 1st 2000",
|
|
"dataset": "Weather"
|
|
}
|
|
],
|
|
"Count": 1
|
|
}
|
|
},
|
|
{
|
|
"markdown": "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",
|
|
"tab": "Scalar",
|
|
"section": "Iff",
|
|
"exercises": {
|
|
"value": [
|
|
{
|
|
"name": "IffEx1",
|
|
"question": "Extend a new column that will check if its raining or not based on the Rain value is greater than 0.",
|
|
"dataset": "Weather",
|
|
"answer": "V2VhdGhlcgp8IGV4dGVuZCBpc3JhaW5pbmcgPSBpZmYoUmFpbiA+IDAsICJyYWluaW5nIiwgIm5vdCByYWluaW5nIik="
|
|
}
|
|
],
|
|
"Count": 1
|
|
}
|
|
},
|
|
{
|
|
"markdown": "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",
|
|
"tab": "Scalar",
|
|
"section": "Sort",
|
|
"exercises": {
|
|
"value": [
|
|
{
|
|
"name": "SortEx1",
|
|
"question": "Sort Weather results by amount of Rain from most to least",
|
|
"dataset": "Weather",
|
|
"answer": "V2VhdGhlcgp8IHNvcnQgYnkgUmFpbiBkZXNj"
|
|
}
|
|
],
|
|
"Count": 1
|
|
}
|
|
},
|
|
{
|
|
"markdown": "RG9jdW1lbnRhdGlvbjogaHR0cHM6Ly9kb2NzLm1pY3Jvc29mdC5jb20vZW4tdXMvYXp1cmUvZGF0YS1leHBsb3Jlci9rdXN0by9xdWVyeS9wYXJzZWpzb25mdW5jdGlvblx1MDAzY2JyL1x1MDAzZVx1MDAzY2JyL1x1MDAzZQ0KDQpUaGUgdG9keW5hbWljKCkgb3BlcmF0b3IgaW50ZXJwcmV0cyBhIHN0cmluZyBhcyBhIEpTT04gdmFsdWUgYW5kIHJldHVybnMgdGhlIHZhbHVlIGFzIGR5bmFtaWMuIFdvcmtzIHNpbWlsaWxhcmx5IGFzIHRoZSBwYXJzZV9qc29uIG9wZXJhdG9yLg0KDQpFeGFtcGxlOg0KZXh0ZW5kIFZhcmlhYmxlID0gcGFyc2VfanNvbihuZXN0ZWRKc29uSXRlbSksIGV4dGVuZCBWYXJpYWJsZSA9IHRvZHluYW1pYyhuZXN0ZWRKc29uSXRlbSlcdTAwM2Nici9cdTAwM2U=",
|
|
"tab": "Scalar",
|
|
"section": "ToDynamic",
|
|
"exercises": {
|
|
"value": [
|
|
{
|
|
"name": "ToDynamicEx1",
|
|
"question": "Convert WinEvents from the table \u0027Events\u0027 to dynamic. Extend a new column called EventID and reference the EventID from WinEvents. Then return rows that have an EventID of 1102. Ensure your Output looks like the output in the \u0027expected result\u0027.",
|
|
"dataset": "Events",
|
|
"answer": "RXZlbnRzCnwgZXh0ZW5kIFdpbkV2ZW50cyA9IHRvZHluYW1pYyhXaW5FdmVudHMpCnwgZXh0ZW5kIEV2ZW50SUQgPSBXaW5FdmVudHMuRXZlbnRJRAp8IHdoZXJlIEV2ZW50SUQgPT0gIjExMDIi"
|
|
}
|
|
],
|
|
"Count": 1
|
|
}
|
|
},
|
|
{
|
|
"markdown": "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",
|
|
"tab": "Advanced",
|
|
"section": "Arg_max",
|
|
"exercises": {
|
|
"value": [
|
|
{
|
|
"name": "Arg_maxEx1",
|
|
"question": "Return the records from each Location with the most Rain for that Location sorted from most Rain to least",
|
|
"dataset": "Weather",
|
|
"answer": "V2VhdGhlcgp8IHN1bW1hcml6ZSBhcmdfbWF4KFJhaW4sICopIGJ5IExvY2F0aW9uCnwgc29ydCBieSBSYWluIGRlc2M="
|
|
},
|
|
{
|
|
"name": "Arg_maxEx2",
|
|
"question": "Return the amount of Rain and TimeGenerated from each Location with the most Rain for that Location sorted from most Rain to least",
|
|
"dataset": "Weather",
|
|
"answer": "V2VhdGhlcgp8IHN1bW1hcml6ZSBhcmdfbWF4KFJhaW4sIFJhaW4sIFRpbWVHZW5lcmF0ZWQpIGJ5IExvY2F0aW9uCnwgc29ydCBieSBSYWluIGRlc2M="
|
|
}
|
|
],
|
|
"Count": 2
|
|
}
|
|
},
|
|
{
|
|
"markdown": "IVtEb2N1bWVudGF0aW9uXShodHRwczovL3NoaWVsZHMuaW8vYmFkZ2UvLURvY3VtZW50YXRpb24taW5mb3JtYXRpb25hbCkNCjxwPg0KaHR0cHM6Ly9kb2NzLm1pY3Jvc29mdC5jb20vZW4tdXMvYXp1cmUvZGF0YS1leHBsb3Jlci9rdXN0by9xdWVyeS9hcmctbWluLWFnZ2Z1bmN0aW9uDQoNCjwvcD4NCg0KICoqU3VtbWFyeToqKg0KPHA+DQpUaGUgYXJnX21pbiBvcGVyYXRvciBmaW5kcyBhIHJvdyBpbiBhIGdyb3VwIHRoYXQgbWluaW1pemVzIGEgc3BlY2lmaWVkIGV4cHJlc2lzb24gYW5kIHJldHVybnMgdGhlIHZhbHVlIG9mIHRoZSBleHByZXNzaW9uIHRvIHJldHVybi4gPC9icj4NCkV4YW1wbGU6IHN1bW1hcml6ZSBbKE5hbWVFeHByVG9NaW5pbWl6ZSAsIE5hbWVFeHByVG9SZXR1cm4gWywgLi4uXSApPV0gYXJnX21pbiAoRXhwclRvTWluaW1pemUsIHwgRXhwclRvUmV0dXJuIFssIC4uLl0pDQo8L3A+DQpFeHByVG9NaW5pbWl6ZTogRXhwcmVzc2lvbiB0aGF0IHdpbGwgYmUgdXNlZCBmb3IgYWdncmVnYXRpb24gY2FsY3VsYXRpb24uIDwvYnI+DQpFeHByVG9SZXR1cm46IEV4cHJlc3Npb24gdGhhdCB3aWxsIGJlIHVzZWQgZm9yIHJldHVybmluZyB0aGUgdmFsdWUgd2hlbiBFeHByVG9NaW5pbWl6ZSBpcyBtaW5pbXVtLiBFeHByZXNzaW9uIHRvIHJldHVybiBtYXkgYmUgYSB3aWxkY2FyZCAoKSB0byByZXR1cm4gYWxsIGNvbHVtbnMgb2YgdGhlIGlucHV0IHRhYmxlLiANCjwvcD4NCg0KICoqRXhhbXBsZToqKg0KPHA+DQpTZWN1cml0eUV2ZW50IHwgc3VtbWFyaXplIGFyZ19taW4oQ29tcHV0ZXIsIEV2ZW50SUQpICA8L2JyPg0KDQpTaWduaW5Mb2dzIHwgc3VtbWFyaXplIGFyZ19taW4oVGltZUdlbmVyYXRlZCwgVXNlckRpc3BsYXlOYW1lKSA8L2JyPg0KPC9wPg0KDQogKipXaGVuIHRvIHVzZToqKg0KPHA+DQphcmdfbWluIGlzIGJlc3QgdXNlZCB3aGVuIGxvb2tpbmcgdG8gcmV0dXJuIHRoZSBoaWdoZXN0IG9yIG1vc3QgcmVjZW50IGxvZyBmb3IgYSBzcGVjaWZpZWQgaXRlbS4gVGhlIG1vc3QgY29tbW9uIHVzZSBmb3IgdGhpcyBvcGVyYXRvciBpcyB0byBmaW5kIHRoZSBtb3N0IHJlY2VudCBsb2cgaW5nZXN0ZWQgZnJvbSBhIHNvdXJjZS4gVGhpcyBjYW4gYmUgdXNlZnVsIHdoZW4gcnVubmluZyBjb25uZWN0b3IgaGVhbHRoIGNoZWNrcywgcmVzb3J1Y2UgcmVwb3J0aW5nIGhlYWx0aCBjaGVja3MsIGFuZCBmaW5kaW5nIG1vc3QgcmVjZW50IGFjdGl2aXR5IG9uIGVudGl0aWVzIG9yIGV2ZW50cy4NCjwvcD4NCg==",
|
|
"tab": "Advanced",
|
|
"section": "Arg_min",
|
|
"exercises": {
|
|
"value": [
|
|
{
|
|
"name": "ArgMinEx1",
|
|
"question": "Return the records from each Location with the lowest High temperature for that Location ordered by High from lowest to highest",
|
|
"dataset": "Weather",
|
|
"answer": "V2VhdGhlcgp8IHN1bW1hcml6ZSBhcmdfbWluKEhpZ2gsICopIGJ5IExvY2F0aW9uCnwgc29ydCBieSBIaWdoIGFzYw=="
|
|
},
|
|
{
|
|
"name": "ArgMinEx2",
|
|
"question": "Return the High and Low temperatures from each Location with the lowest High temperature for that Location ordered by High from lowest to highest",
|
|
"dataset": "Weather",
|
|
"answer": "V2VhdGhlcgp8IHN1bW1hcml6ZSBhcmdfbWluKEhpZ2gsIExvdykgYnkgTG9jYXRpb24KfCBzb3J0IGJ5IEhpZ2ggYXNj"
|
|
}
|
|
],
|
|
"Count": 2
|
|
}
|
|
},
|
|
{
|
|
"markdown": "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",
|
|
"tab": "Advanced",
|
|
"section": "Dcount",
|
|
"exercises": {
|
|
"value": [
|
|
{
|
|
"name": "DcountEx1",
|
|
"question": "Return unique Low temperatures and group the count by location",
|
|
"dataset": "Weather",
|
|
"answer": "V2VhdGhlcgp8IHN1bW1hcml6ZSBMb3dzID0gZGNvdW50KExvdykgYnkgTG9jYXRpb24="
|
|
},
|
|
{
|
|
"name": "DcountEx2",
|
|
"question": "Return the number of distinct locations for each High in Weather sorted from most to least counts and highest to lowest temperatures",
|
|
"dataset": "Weather",
|
|
"answer": "V2VhdGhlcgp8IHN1bW1hcml6ZSBkY291bnQoTG9jYXRpb24pIGJ5IEhpZ2gKfCBzb3J0IGJ5IGRjb3VudF9Mb2NhdGlvbiBkZXNjLCBIaWdoIGRlc2M="
|
|
}
|
|
],
|
|
"Count": 1
|
|
}
|
|
},
|
|
{
|
|
"markdown": "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",
|
|
"tab": "Advanced",
|
|
"section": "Dcountif",
|
|
"exercises": {
|
|
"value": [
|
|
{
|
|
"name": "DcountifEx1",
|
|
"question": "Return the number of distinct locations for each High in Weather if there was Rain that day sorted from most to least counts and highest to lowest temperatures",
|
|
"dataset": "Weather",
|
|
"answer": "V2VhdGhlcgp8IHdoZXJlIFJhaW4gPiAwCnwgc3VtbWFyaXplIGRjb3VudChMb2NhdGlvbikgYnkgSGlnaAp8IHNvcnQgYnkgZGNvdW50X0xvY2F0aW9uIGRlc2MsIEhpZ2ggZGVzYw=="
|
|
}
|
|
],
|
|
"Count": 1
|
|
}
|
|
},
|
|
{
|
|
"markdown": "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",
|
|
"tab": "Advanced",
|
|
"section": "Max",
|
|
"exercises": {
|
|
"value": [
|
|
{
|
|
"name": "MaxEx1",
|
|
"question": "Return the hottest High temperature in Weather",
|
|
"dataset": "Weather",
|
|
"answer": "V2VhdGhlcgp8IHN1bW1hcml6ZSBtYXgoSGlnaCk="
|
|
}
|
|
],
|
|
"Count": 1
|
|
}
|
|
},
|
|
{
|
|
"markdown": "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",
|
|
"tab": "Advanced",
|
|
"section": "Min",
|
|
"exercises": {
|
|
"value": [
|
|
{
|
|
"name": "MinEx1",
|
|
"question": "Return the coldest Low temperature in Weather",
|
|
"dataset": "Weather",
|
|
"answer": "V2VhdGhlcgp8IHN1bW1hcml6ZSBtaW4oTG93KQ=="
|
|
}
|
|
],
|
|
"Count": 1
|
|
}
|
|
},
|
|
{
|
|
"markdown": "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",
|
|
"tab": "Advanced",
|
|
"section": "Mvexpand",
|
|
"exercises": {
|
|
"value": [
|
|
{
|
|
"name": "MvexpandEx1",
|
|
"question": "Use mvexpand to expand the name column in the \u0027shapes\u0027 table to individual rows.",
|
|
"dataset": "shapes",
|
|
"answer": "c2hhcGVzCnwgbXZleHBhbmQgbmFtZQ=="
|
|
},
|
|
{
|
|
"name": "MvexpandEx2",
|
|
"question": "Use mvexpand to expand `kids` from the `parents` table.",
|
|
"dataset": "parents",
|
|
"answer": "cGFyZW50cwp8IG12LWV4cGFuZCBraWRz"
|
|
}
|
|
],
|
|
"Count": 2
|
|
}
|
|
},
|
|
{
|
|
"markdown": "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",
|
|
"tab": "Dataset",
|
|
"section": "Datatable",
|
|
"exercises": {
|
|
"value": [
|
|
{
|
|
"name": "DatatableEx1",
|
|
"question": "Create a custom datatable of cities with Location of Boston, Chicago, and Portland",
|
|
"dataset": "",
|
|
"answer": "ZGF0YXRhYmxlIChMb2NhdGlvbjpzdHJpbmcpIFsKICAgICJCb3N0b24iLCJDaGljYWdvIiwiUG9ydGxhbmQiCl0="
|
|
}
|
|
],
|
|
"Count": 1
|
|
}
|
|
},
|
|
{
|
|
"markdown": "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",
|
|
"tab": "Dataset",
|
|
"section": "Let",
|
|
"exercises": {
|
|
"value": [
|
|
{
|
|
"name": "LetEx1",
|
|
"question": "Create a variable called SeattleLows and set its value to be all cold temperatures for Seattle. Print the value of the variable in descending order.",
|
|
"dataset": "Weather",
|
|
"answer": "IGxldCBTZWF0dGxlTG93cyA9IFdlYXRoZXIgfCB3aGVyZSBMb2NhdGlvbiA9PSAnU2VhdHRsZScgfCBzdW1tYXJpemUgYnkgTG93IHwgb3JkZXIgYnkgTG93IGRlc2M7IFNlYXR0bGVMb3dz"
|
|
},
|
|
{
|
|
"name": "LetEx2",
|
|
"question": "create two variables called startTime and endTime. Set startTime to be 06/26/2015 and endTime to be 06/27/2015. Return all results for New York City during that time. Note: datetime uses UTC so there may be a 7 hour time difference in the logs generated. If you see results from 06/22, add 7 hours to startTime to remove the extras.",
|
|
"dataset": "Weather",
|
|
"answer": "bGV0IHN0YXJ0VGltZSA9IGRhdGV0aW1lKDA2LzIzLzIwMTUgMDc6MDA6MDApOyBsZXQgZW5kVGltZSA9IGRhdGV0aW1lKDA2LzI1LzIwMTUgMDA6MDA6MDApOyBXZWF0aGVyIHwgd2hlcmUgVGltZUdlbmVyYXRlZCBiZXR3ZWVuKHN0YXJ0VGltZS4uZW5kVGltZSkgfCB3aGVyZSBMb2NhdGlvbiA9PSAnTmV3IFlvcmsgQ2l0eSc="
|
|
}
|
|
],
|
|
"Count": 1
|
|
}
|
|
},
|
|
{
|
|
"markdown": "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",
|
|
"tab": "Dataset",
|
|
"section": "Extend",
|
|
"exercises": {
|
|
"value": [
|
|
{
|
|
"name": "ExtendEx1",
|
|
"question": "Add a Range column to Weather that contains the difference between High and Low temperatures",
|
|
"dataset": "Weather",
|
|
"answer": "V2VhdGhlcgp8IGV4dGVuZCBSYW5nZSA9IEhpZ2gtTG93"
|
|
}
|
|
],
|
|
"Count": 1
|
|
}
|
|
},
|
|
{
|
|
"markdown": "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",
|
|
"tab": "Dataset",
|
|
"section": "Union",
|
|
"exercises": {
|
|
"value": [
|
|
{
|
|
"name": "UnionEx1",
|
|
"question": "Combine these two cities datatables into a single datatable using the union statement\u003cbr/\u003elet cities1 = datatable(Location:string)[\"Boston\",\"Eugene\",\"Houston\"];\u003cbr/\u003elet cities2 = datatable(Location:string)[\"Boise\",\"Chicago\",\"Tampa\"];",
|
|
"dataset": "",
|
|
"answer": "bGV0IGNpdGllczEgPSBkYXRhdGFibGUoTG9jYXRpb246c3RyaW5nKVsiQm9zdG9uIiwiRXVnZW5lIiwiSG91c3RvbiJdOwpsZXQgY2l0aWVzMiA9IGRhdGF0YWJsZShMb2NhdGlvbjpzdHJpbmcpWyJCb2lzZSIsIkNoaWNhZ28iLCJUYW1wYSJdOwpjaXRpZXMxCnwgdW5pb24gY2l0aWVzMg=="
|
|
}
|
|
],
|
|
"Count": 1
|
|
}
|
|
},
|
|
{
|
|
"markdown": "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",
|
|
"tab": "Dataset",
|
|
"section": "Join",
|
|
"exercises": {
|
|
"value": [
|
|
{
|
|
"name": "JoinEx1",
|
|
"question": "Add state data to the Weather table with a left inner join using the following states datatable\u003cbr/\u003elet states = datatable(Location:string,State:string)[\"Houston\",\"TX\",\"Philadelphia\",\"PA\",\"Indianapolis\",\"IN\",\"New York City\",\"NY\",\"Seattle\",\"WA\"];",
|
|
"dataset": "Weather",
|
|
"answer": "bGV0IHN0YXRlcyA9IGRhdGF0YWJsZShMb2NhdGlvbjpzdHJpbmcsU3RhdGU6c3RyaW5nKVsiSG91c3RvbiIsIlRYIiwiUGhpbGFkZWxwaGlhIiwiUEEiLCJJbmRpYW5hcG9saXMiLCJJTiIsIk5ldyBZb3JrIENpdHkiLCJOWSIsIlNlYXR0bGUiLCJXQSJdOwpXZWF0aGVyCnwgam9pbiBzdGF0ZXMgb24gTG9jYXRpb24sICRsZWZ0LkxvY2F0aW9uID09ICRyaWdodC5Mb2NhdGlvbg=="
|
|
}
|
|
],
|
|
"Count": 1
|
|
}
|
|
},
|
|
{
|
|
"markdown": "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",
|
|
"tab": "External",
|
|
"section": "ExternalData",
|
|
"exercises": {
|
|
"value": [
|
|
{
|
|
"name": "ExternalDataEx1",
|
|
"question": "Return a new datatable based on the following TIC 3.0 mapping CSV\u003cbr/\u003ehttps://raw.githubusercontent.com/Azure/Azure-Sentinel/master/Sample%20Data/Feeds/ZeroTrustTIC3Mapping.csv",
|
|
"dataset": "",
|
|
"answer": "bGV0IEV4dGVybmFsVGFibGUgPSBleHRlcm5hbGRhdGEoUmVjb21tZW5kYXRpb25EaXNwbGF5TmFtZTpzdHJpbmcsIENhcGJpbGl0eTpzdHJpbmcsIEZhbWlseTpzdHJpbmcpCltAJ2h0dHBzOi8vcmF3LmdpdGh1YnVzZXJjb250ZW50LmNvbS90ZWFjaGppbmcvVGVhY2hKaW5nLVdvcmtib29rcy9tYWluL0RhdGFzZXRzL1plcm9UcnVzdFRJQzNNYXBwaW5nLmNzdiddCndpdGggKGZvcm1hdD1jc3YpOwpFeHRlcm5hbFRhYmxl"
|
|
}
|
|
],
|
|
"Count": 1
|
|
}
|
|
}
|
|
]
|