modin.pandas.DataFrame.info¶

DataFrame.info(verbose: bool | None = None, buf: IO[str] | None = None, max_cols: int | None = None, memory_usage: bool | str | None = None, show_counts: bool | None = None, null_counts: bool | None = None)[source]¶

Print a concise summary of the DataFrame. Snowflake DataFrames mirror the output of pandas df.info but with some specific limitations ( zeroed memory usage, no index information ).

Parameters:

  • verbose (bool, optional) – Whether to print the full summary. By default, the setting in pandas.options.display.max_info_columns is followed.

  • buf (writable buffer, defaults to sys.stdout) – Where to send the output. By default, the output is printed to sys.stdout. Pass a writable buffer if you need to further process the output.

  • max_cols (int, optional) – When to switch from the verbose to the truncated output. If the DataFrame has more than max_cols columns, the truncated output is used. By default, the setting in pandas.options.display.max_info_columns is used.

  • memory_usage (bool, str, optional) – Displays 0 for memory usage, since the memory usage of a snowflake dataframe is remote and partially indeterminant.

  • show_counts (bool, optional) – Whether to show the non-null counts. By default, this is shown only if the DataFrame is smaller than pandas.options.display.max_info_rows and pandas.options.display.max_info_columns. A value of True always shows the counts, and False never shows the counts.

Returns:

This method prints a summary of a DataFrame and returns None.

Return type:

None

Examples

>>> df = pd.DataFrame({'COL1': [1, 2, 3],
...                    'COL2': ['A', 'B', 'C']})
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>>> df.info() 
<class 'modin.pandas.dataframe.DataFrame'>
SnowflakeIndex
Data columns (total 2 columns):
 #   Column  Non-Null Count  Dtype
---  ------  --------------  -----
 0   COL1    3 non-null      int64
 1   COL2    3 non-null      object
dtypes: int64(1), object(1)
memory usage: 0.0 bytes
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