En100882pdfdownload
En100882pdfdownload

En100882pdfdownload
tag:
En100882pdfdownloadimport {div} from ‘@klarna/svelte’
import {Button} from ‘@klarna/svelte/src/components/Button’
import {Row} from ‘@klarna/svelte/src/components/Row’
export default div`
.pb-page–back-up-order {
align-items: center;
flex-direction: row;
justify-content: flex-start;
}
.pb-page–back-up-order__item {
border-radius: 10px;
display: flex;
flex-direction: row;
padding: 8px 0;
text-align: center;
&:last-child {
border-right: 1px solid ${colors.gray};
flex-grow: 1;
}
&__name {
display: inline-block;
width: 200px;
}
&__quantity {
font-size: 10px;
margin-bottom: 4px;
}
}
`
Q:
What is the “hidden” wrapper pyspark.sql.dataframe.DataFrame
I am trying to understand DataFrames and Spark SQL.
This is the example I was referring to
# Create a DataFrame object from Spark SQL query
df_spark = spark.createDataFrame(
[(1, “a”), (2, “b”), (3, “c”)], [“id”, “data”])
This is my understanding of a DataFrame object:
df_spark is a class in Python which has an __init__ method and it can be used as a stand alone object like this:
>>> df_spark.show()
+—-+—+
| id | |
+—-+—+
| 1| a|
| 2| b|
| 3| c|
+
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