I have a dictionary:
DICT = {
"A": (0, 100),
"B": (100, 200),
"C": (300, 400),
"D": (400, 500),
}
which looks like:
{'A': (0, 100), 'B': (100, 200), 'C': (300, 400), 'D': (400, 500)}
Ultimately, I would like to convert this to a Spark dataframe, looking like this:
category lower_bound upper_bound
A 0 100
B 100 200
C 300 400
D 400 500
This is attainable if I use:
r = (
pd.DataFrame.from_dict(DICT, orient="index")
.reset_index()
.rename(columns={"index": "category", 0: "lower", 1: "upper"})
)
Is there a way I can directly create a Spark Dataframe from the dictionary that is oriented that way?
Found the solution using this answer
df = spark.createDataFrame(
[[x[0], *x[1]] for x in DICT.items()], ["category", "lower_bound", "upper_bound"]
)
```
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