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add delimiter option for solving read error #183

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merged 1 commit into from
Nov 4, 2022
Merged

add delimiter option for solving read error #183

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4 changes: 2 additions & 2 deletions docs/StardustDocs/topics/KPropertiesApi.md
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Original file line number Diff line number Diff line change
Expand Up @@ -15,7 +15,7 @@ data class Passenger(
val lastName: String
)

val passengers = DataFrame.read("titanic.csv")
val passengers = DataFrame.read("titanic.csv", delimiter = ';')
.add(Passenger::lastName) { "name"<String>().split(",").last() }
.dropNulls(Passenger::age)
.filter {
Expand All @@ -39,7 +39,7 @@ data class Passenger(
val name: String
)

val passengers = DataFrame.read("titanic.csv")
val passengers = DataFrame.read("titanic.csv", delimiter = ';')
.filter { it.get(Passenger::city).endsWith("NY") }
.toListOf<Passenger>()
```
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8 changes: 4 additions & 4 deletions docs/StardustDocs/topics/apiLevels.md
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Expand Up @@ -34,7 +34,7 @@ In the most of the code snippets in this documentation there's a tab selector th
<!---FUN extensionProperties1-->

```kotlin
val df = DataFrame.read("titanic.csv")
val df = DataFrame.read("titanic.csv", delimiter = ';')
```

<!---END-->
Expand All @@ -55,7 +55,7 @@ df.add("lastName") { name.split(",").last() }
<!---FUN strings-->

```kotlin
DataFrame.read("titanic.csv")
DataFrame.read("titanic.csv", delimiter = ';')
.add("lastName") { "name"<String>().split(",").last() }
.dropNulls("age")
.filter {
Expand All @@ -79,7 +79,7 @@ val age by column<Int?>()
val name by column<String>()
val lastName by column<String>()

DataFrame.read("titanic.csv")
DataFrame.read("titanic.csv", delimiter = ';')
.add(lastName) { name().split(",").last() }
.dropNulls { age }
.filter { survived() && home().endsWith("NY") && age()!! in 10..20 }
Expand All @@ -100,7 +100,7 @@ data class Passenger(
val lastName: String
)

val passengers = DataFrame.read("titanic.csv")
val passengers = DataFrame.read("titanic.csv", delimiter = ';')
.add(Passenger::lastName) { "name"<String>().split(",").last() }
.dropNulls(Passenger::age)
.filter {
Expand Down
2 changes: 1 addition & 1 deletion docs/StardustDocs/topics/columnAccessorsApi.md
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Expand Up @@ -21,7 +21,7 @@ Now columns can be accessed in a type-safe way using `invoke` operator:
<!---FUN accessors2-->

```kotlin
DataFrame.read("titanic.csv")
DataFrame.read("titanic.csv", delimiter = ';')
.add(lastName) { name().split(",").last() }
.dropNulls { age }
.filter { survived() && home().endsWith("NY") && age()!! in 10..20 }
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2 changes: 1 addition & 1 deletion docs/StardustDocs/topics/extensionPropertiesApi.md
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Expand Up @@ -7,7 +7,7 @@ When `DataFrame` is used within Jupyter Notebooks or Datalore with Kotlin Kernel
<!---FUN extensionProperties1-->

```kotlin
val df = DataFrame.read("titanic.csv")
val df = DataFrame.read("titanic.csv", delimiter = ';')
```

<!---END-->
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3 changes: 2 additions & 1 deletion docs/StardustDocs/topics/overview.md
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Expand Up @@ -31,8 +31,9 @@ The handiness of this abstraction is not in the table itself but in a set of ope
**Basics:**

```kotlin
val df = DataFrame.read("titanic.csv")
val df = DataFrame.read("titanic.csv", delimiter = ';')
```

```kotlin
// filter rows
df.filter { survived && home.endsWith("NY") && age in 10..20 }
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2 changes: 1 addition & 1 deletion docs/StardustDocs/topics/stringApi.md
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Expand Up @@ -7,7 +7,7 @@ String column names are the easiest way to access data in DataFrame:
<!---FUN strings-->

```kotlin
DataFrame.read("titanic.csv")
DataFrame.read("titanic.csv", delimiter = ';')
.add("lastName") { "name"<String>().split(",").last() }
.dropNulls("age")
.filter {
Expand Down