typos in comments and docs

awswrangler/s3/_read_parquet.py

@@ -708,14 +708,14 @@ def read_parquet(
     Reading in chunks (Chunk by file)
 
     >>> import awswrangler as wr
-    >>> dfs = wr.s3.read_parquet(path=['s3://bucket/filename0.csv', 's3://bucket/filename1.csv'], chunked=True)
+    >>> dfs = wr.s3.read_parquet(path=['s3://bucket/filename0.parquet', 's3://bucket/filename1.parquet'], chunked=True)
     >>> for df in dfs:
     >>>     print(df)  # Smaller Pandas DataFrame
 
     Reading in chunks (Chunk by 1MM rows)
 
     >>> import awswrangler as wr
-    >>> dfs = wr.s3.read_parquet(path=['s3://bucket/filename0.csv', 's3://bucket/filename1.csv'], chunked=1_000_000)
+    >>> dfs = wr.s3.read_parquet(path=['s3://bucket/filename0.parquet', 's3://bucket/filename1.parquet'], chunked=1_000_000)
     >>> for df in dfs:
     >>>     print(df)  # 1MM Pandas DataFrame
 
@@ -849,7 +849,7 @@ def read_parquet_table(
         Suffix or List of suffixes to be read (e.g. [".gz.parquet", ".snappy.parquet"]).
         If None, will try to read all files. (default)
     filename_ignore_suffix: Union[str, List[str], None]
-        Suffix or List of suffixes for S3 keys to be ignored.(e.g. [".csv", "_SUCCESS"]).
+        Suffix or List of suffixes for S3 keys to be ignored.(e.g. [".parquet", "_SUCCESS"]).
         If None, will try to read all files. (default)
     catalog_id : str, optional
         The ID of the Data Catalog from which to retrieve Databases.