[SPARK-56255][PYTHON][CONNECT] Make spark.read.csv accept DataFrame input

[Yicong-Huang]

What changes were proposed in this pull request?

This PR adds support for passing a DataFrame containing CSV strings directly to spark.read.csv(), following the same pattern established by #55097 (SPARK-56253) for spark.read.json().

Why are the changes needed?

Adding DataFrame support to csv() makes the API consistent with json() and enables Connect-compatible CSV parsing without sc.parallelize().

Does this PR introduce any user-facing change?

Yes. spark.read.csv() now accepts a DataFrame with a single string column as input, in addition to the existing str, list, and RDD inputs.

csv_df = spark.createDataFrame([("Alice,25",), ("Bob,30",)], schema="value STRING")
spark.read.csv(csv_df, schema="name STRING, age INT").show()
# +-----+---+
# | name|age|
# +-----+---+
# |Alice| 25|
# |  Bob| 30|
# +-----+---+

How was this patch tested?

Added 10 new test cases.

Was this patch authored or co-authored using generative AI tooling?

No.

[HyukjinKwon]

I think it's safer to add this if dataframe check first with return to avoid any behaviour changes. e.g., we might support sth else than list.

[Yicong-Huang]

Make sense. moved the check up.

[HyukjinKwon]

Shall we fix the same as 638ca41?

[Yicong-Huang]

Done. Applied the same pattern to reject multi-column input.

[hvanhovell]

This the same code as above. Create a util for this?

[Yicong-Huang]

Makes sense. Extracted a helper method.

[HyukjinKwon]

Merged to master.