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Added a link to the missed datset titanic.csv (#389)
* Add the dataset used in the documentation * Added the links to the dataset
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data/titanic.csv

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docs/StardustDocs/topics/KPropertiesApi.md

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```
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<!---END-->
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The `titanic.csv` file could be found [here](https://github.com/Kotlin/dataframe/blob/master/data/titanic.csv).

docs/StardustDocs/topics/apiLevels.md

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</tabs>
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The `titanic.csv` file could be found [here](https://github.com/Kotlin/dataframe/blob/master/data/titanic.csv).
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# Comparing the APIs
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The [String API](stringApi.md) is the simplest and unsafest of them all. The main advantage of it is that it can be

docs/StardustDocs/topics/columnAccessorsApi.md

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The `titanic.csv` file could be found [here](https://github.com/Kotlin/dataframe/blob/master/data/titanic.csv).
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<warning>
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Note that it still doesn’t solve the problem of whether the column actually exists in a data frame, but reduces type casting.
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</warning>

docs/StardustDocs/topics/extensionPropertiesApi.md

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The `titanic.csv` file could be found [here](https://github.com/Kotlin/dataframe/blob/master/data/titanic.csv).
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In notebooks, extension properties are generated for [`DataSchema`](schemas.md) that is extracted from [`DataFrame`](DataFrame.md)
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instance after REPL line execution.
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After that [`DataFrame`](DataFrame.md) variable is typed with its own [`DataSchema`](schemas.md), so only valid extension properties corresponding to actual columns in DataFrame will be allowed by the compiler and suggested by completion.

docs/StardustDocs/topics/overview.md

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}
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```
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The `titanic.csv` file could be found [here](https://github.com/Kotlin/dataframe/blob/master/data/titanic.csv).
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**Create:**
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```kotlin
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// create columns

docs/StardustDocs/topics/stringApi.md

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The `titanic.csv` file could be found [here](https://github.com/Kotlin/dataframe/blob/master/data/titanic.csv).
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<warning>
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Note that if data frame doesn’t contain column with the string provided, or you try to cast to the wrong type it will lead to runtime exception.
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</warning>

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