fix: review comments

docs/getting_started.rst

@@ -103,15 +103,15 @@ With a :class:`.DataFrameClient` object, you can:
 Pandas Utility
 ~~~~~~~~~~~~~~
 
-Utility functions for managing Pandas DataFrames and interacting with the DataFrame API include:
+Utility functions to interact with :class:`.DataFrameClient` using [pandas.DataFrame](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.html)
 
-* Create a table from a pandas dataframe.
+* Create a table from a `pandas.DataFrame`.
 
-* Append pandas dataframe to an existing table.
+* Append `pandas.DataFrame` to an existing table.
 
-* Query decimated data from a table as pandas dataframe.
+* Query decimated data from a table as `pandas.DataFrame`.
 
-* Query data from a table as pandas dataframe.
+* Query data from a table as `pandas.DataFrame`.
 
 Examples
 ~~~~~~~~
@@ -134,7 +134,7 @@ Export data from a table
    :language: python
    :linenos:
 
-Table operations using pandas dataframe
+Table operations using [pandas.DataFrame](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.html)
 
 .. literalinclude:: ../examples/dataframe/pandas_dataframe_operations.py
    :language: python

examples/dataframe/pandas_dataframe_operations.py

@@ -1,6 +1,5 @@
 import pandas as pd
 from nisystemlink.clients.dataframe import DataFrameClient
-from nisystemlink.clients.core import HttpConfiguration
 from nisystemlink.clients.dataframe.models import (
     DecimationMethod,
     DecimationOptions,
@@ -21,7 +20,10 @@
     data=[[1, 2, 3], [4, 5, 6], [7, 8, 9]], columns=["a", "b", "c"]
 )
 df.set_index("a", inplace=True)
+print(df)
 
+print(client.list_tables())
+client.list_tables()
 try:
     table_id = create_table_from_pandas_df(
         client, df, "Example Table", nullable_columns=False
@@ -55,4 +57,4 @@
 print("Queried table data as pandas dataframe:")
 print(queried_df)
 
-client.delete_table(table_id)
+client.delete_table(table_id)

nisystemlink/clients/dataframe/models/_data_frame.py

@@ -53,7 +53,7 @@ class DataFrame(JsonModel):
     columns: Optional[List[str]] = None
     """The names and order of the columns included in the data frame."""
 
-    data: List[List[Optional[str]]] = None
+    data: Optional[List[List[Optional[str]]]] = None
     """The data for each row with the order specified in the columns property.
     Must contain a value for each column in the columns property."""
 

nisystemlink/clients/dataframe/utilities/_pandas_dataframe_operations.py

@@ -1,3 +1,5 @@
+from typing import Optional
+
 import pandas as pd
 from nisystemlink.clients.dataframe import DataFrameClient
 from nisystemlink.clients.dataframe.models import (
@@ -24,7 +26,7 @@ def create_table_from_pandas_df(
         client (DataFrameClient): Instance of DataFrameClient.
         df (pd.DataFrame): Pandas dataframe.
         table_name (str): Name of the table.
-        nullable_columns (bool): Make the columns nullable.
+        nullable_columns (bool): Make the columns nullable. Nullable columns can contain `null` values.
 
     Returns:
         str: ID of the table.
@@ -42,7 +44,10 @@ def create_table_from_pandas_df(
 
 
 def append_pandas_df_to_table(
-    client: DataFrameClient, table_id: str, df: pd.DataFrame
+    client: DataFrameClient,
+    table_id: str,
+    df: pd.DataFrame,
+    end_of_data: Optional[bool] = None,
 ) -> None:
     """Append `df` to table.
 
@@ -54,12 +59,48 @@ def append_pandas_df_to_table(
     Returns:
         None
     """
-    frame = DataFrame()
+    frame: DataFrame = DataFrame()
     frame.from_pandas(df)
     client.append_table_data(
-        id=table_id, data=AppendTableDataRequest(frame=frame, end_of_data=False)
+        id=table_id, data=AppendTableDataRequest(frame=frame, end_of_data=end_of_data)
+    )
+
+
+def create_table_with_data_from_pandas_df(
+    client: DataFrameClient,
+    df: pd.DataFrame,
+    table_name: str,
+    nullable_columns: bool,
+    batch_size: int = 1000,
+    end_of_data: Optional[bool] = None,
+) -> str:
+    """Create a table and upload data from a pandas DataFrame.
+
+    This function creates the table, uploads the data (with batching for large data),
+    and closes the upload process in one seamless call.
+
+    Args:
+        client (DataFrameClient): Instance of DataFrameClient.
+        df (pd.DataFrame): Pandas DataFrame with data to upload.
+        table_name (str): Name of the table to create.
+        nullable_columns (bool): Make the columns nullable. Nullable columns can contain `null` values.
+        batch_size (Optional[int]): Number of rows to batch in each upload. Default is 1000.
+
+    Returns:
+        str: ID of the created table.
+    """
+    table_id = create_table_from_pandas_df(
+        client=client, df=df, table_name=table_name, nullable_columns=nullable_columns
     )
 
+    num_rows = len(df)
+    for start_row in range(0, num_rows, batch_size):
+        end_row = min(start_row + batch_size, num_rows)
+        batch_df = df.iloc[start_row:end_row]
+        append_pandas_df_to_table(client, table_id, batch_df, end_of_data)
+
+    return table_id
+
 
 def query_decimated_table_data_as_pandas_df(
     client: DataFrameClient,
@@ -78,10 +119,10 @@ def query_decimated_table_data_as_pandas_df(
     Returns:
         pd.DataFrame: Table data in pandas dataframe format.
     """
-    index_name: str = None
+    index_name = None
     if index:
         index_name = _get_table_index_name(client=client, table_id=table_id)
-        if query.columns:
+        if query.columns and index_name:
             if index_name not in query.columns:
                 query.columns.append(index_name)
     response = client.query_decimated_data(table_id, query)
@@ -107,11 +148,10 @@ def query_table_data_as_pandas_df(
     """
     continuation_token = None
     all_rows = []
-    index_name: str = None
 
     if index:
         index_name = _get_table_index_name(client=client, table_id=table_id)
-        if query.columns:
+        if query.columns and index_name:
             if index_name not in query.columns:
                 query.columns.append(index_name)
 

nisystemlink/clients/dataframe/utilities/_pandas_exception.py

@@ -1,3 +1,6 @@
+SUPPORTED_INDEX_DATA_TYPE = ["INT32", "INT64", "TIMESTAMP"]
+
+
 class DataFrameError(Exception):
     """Base class for Dataframe errors."""
 
@@ -11,9 +14,8 @@ def __init__(self, index_name: str = None) -> None:
         self.index_name = index_name
         self.message = "Data frame must contain one index."
         if index_name:
-            self.message = (
-                f"Column '{self.index_name}' must be of type INT32, INT64, or TIMESTAMP to be an index column."
-            )
+            self.message = f"Column '{self.index_name}' must be of type {SUPPORTED_INDEX_DATA_TYPE}"
+            " to be an index column."
         super().__init__(self.message)
 
 
@@ -23,5 +25,7 @@ class InvalidColumnTypeError(DataFrameError):
     def __init__(self, column_name: str, column_type: str) -> None:
         self.column_name = column_name
         self.column_type = column_type
-        self.message = f"Column '{column_name}' has an unsupported datatype: {column_type}"
+        self.message = (
+            f"Column '{column_name}' has an unsupported datatype: {column_type}"
+        )
         super().__init__(self.message)

nisystemlink/clients/dataframe/utilities/_pandas_utils.py

@@ -6,11 +6,12 @@
 
 from ._pandas_exception import InvalidColumnTypeError, InvalidIndexError
 
-UNSUPPORTED_PANDAS_INT_TYPES = ["int8", "int16"]
-"""List of unsupported pandas integer types for conversion to `DataType`."""
-
-UNSUPPORTED_PANDAS_FLOAT_TYPES = ["float16"]
-"""List of unsupported pandas float types for conversion to `DataType`."""
+UNSUPPORTED_PANDAS_DATA_TYPE_CONVERSION = {
+    "int8": "int32",
+    "int16": "int32",
+    "float16": "float32",
+}
+"""Mapping of unsupported pandas types to supported data types for `DataType`."""
 
 SUPPORTED_INDEX_DATA_TYPE = [DataType.Int32, DataType.Int64, DataType.Timestamp]
 """List of supported index data types for table creation.
@@ -62,11 +63,8 @@ def _type_cast_column_datatype(
         data = pd.to_numeric(data, downcast="integer")
         pd_dtype = data.dtype
 
-    if pd_dtype in UNSUPPORTED_PANDAS_INT_TYPES:
-        data = data.astype("int32")
-
-    elif pd_dtype in UNSUPPORTED_PANDAS_FLOAT_TYPES:
-        data = data.astype("float32")
+    if pd_dtype in UNSUPPORTED_PANDAS_DATA_TYPE_CONVERSION:
+        data = data.astype(UNSUPPORTED_PANDAS_DATA_TYPE_CONVERSION[pd_dtype])
 
     return data
 
@@ -81,7 +79,7 @@ def _infer_index_column(df: pd.DataFrame) -> Column:
         InvalidIndexError: If multiple index present or index is of unsupported type.
 
     Returns:
-        Column: Valid `Column` to the table.
+        Column: Valid Index `Column` for the table.
     """
     index = df.index.name
 
@@ -140,7 +138,7 @@ def _infer_dataframe_columns(df: pd.DataFrame, nullable_columns: bool) -> List[C
     return columns
 
 
-def _get_table_index_name(client: DataFrameClient, table_id: str) -> str:
+def _get_table_index_name(client: DataFrameClient, table_id: str) -> Optional[str]:
     """Get the index name from the table columns.
 
     Args: