Teradata Package for Python Function Reference on VantageCloud Lake - to_csv - Teradata Package for Python - Look here for syntax, methods and examples for the functions included in the Teradata Package for Python.
Teradata® Package for Python Function Reference on VantageCloud Lake
- Deployment
- VantageCloud
- Edition
- Lake
- Product
- Teradata Package for Python
- Release Number
- 20.00.00.03
- Published
- December 2024
- ft:locale
- en-US
- ft:lastEdition
- 2024-12-19
- dita:id
- TeradataPython_FxRef_Lake_2000
- Product Category
- Teradata Vantage
- teradataml.geospatial.geodataframe.GeoDataFrame.to_csv = to_csv(self, csv_file, num_rows=99999, all_rows=False, fastexport=False, sep=',', quotechar='"', catch_errors_warnings=False, **kwargs)
- DESCRIPTION:
Export data to CSV from teradataml DataFrame with or
without FastExport protocol.
PARAMETERS:
csv_file:
Required Argument.
Specifies the name of CSV file to export the data into.
Types: str
num_rows:
Optional Argument.
Specifies the number of rows to export.
Note:
This argument is ignored if "all_rows" is set to True.
Default Value: 99999
Types: int
all_rows:
Optional Argument.
Specifies whether all rows should be exported to CSV or not.
Default Value: False
Types: bool
fastexport:
Optional Argument.
Specifies whether FastExport protocol should be used or not while
exporting data. When set to True, data is exported using FastExport
protocol, otherwise FastExport protocol is not used, which is default.
When set to None, the approach is decided based on the number of rows
to be exported.
Notes:
1. Teradata recommends to use FastExport when number of rows
in teradataml DataFrame are atleast 100,000. To extract
lesser rows ignore this option and go with regular
approach. FastExport opens multiple data transfer connections
to the database.
2. FastExport does not support all Teradata Database data types.
For example, tables with BLOB and CLOB type columns cannot
be extracted.
3. FastExport cannot be used to extract data from a
volatile or temporary table.
4. For best efficiency, do not use DataFrame.groupby() and
DataFrame.sort() with FastExport.
For additional information about FastExport protocol through
teradatasql driver, please refer to FASTEXPORT section of
https://pypi.org/project/teradatasql/#FastExport driver documentation.
Default Value: False
Types: bool
sep:
Optional Argument.
Specifies a single character string used to separate fields in a CSV file.
Default Value: ","
Notes:
1. "sep" cannot be line feed ('\n') or carriage return ('\r').
2. "sep" should not be same as "quotechar".
3. Length of "sep" argument should be 1.
Types: String
quotechar:
Optional Argument.
Specifies a single character string used to quote fields in a CSV file.
Default Value: """
Notes:
1. "quotechar" cannot be line feed ('\n') or carriage return ('\r').
2. "quotechar" should not be same as "sep".
3. Length of "quotechar" argument should be 1.
Types: String
catch_errors_warnings:
Optional Argument.
Specifies whether to catch errors/warnings (if any) raised by
FastExport protocol while exporting data.
Note:
This argument is ignored if "fastexport" is set to False.
Default Value: False
Types: bool
kwargs:
Optional Argument.
Specifies keyword arguments. Argument "open_sessions" can be
passed as keyword arguments.
* "open_sessions" specifies the number of Teradata data transfer
sessions to be opened for fastexport. This argument is only
applicable in fastexport mode.
Note:
If "open_sessions" argument is not provided, the default value
is the smaller of 8 or the number of AMPs avaialble.
For additional information about number of Teradata data-transfer
sessions opened during fastexport, please refer to:
https://pypi.org/project/teradatasql/#FastExport
RETURNS:
When FastExport protocol is used and "catch_errors_warnings" is set to True,
then the function returns a tuple containing:
a. Errors, if any, thrown by fastexport in a list of strings.
b. Warnings, if any, thrown by fastexport in a list of strings.
RAISES:
TeradataMlException
EXAMPLES:
# Create a teradataml DataFrame.
>>> load_example_data("dataframe","admissions_train")
>>> df = DataFrame("admissions_train")
>>> df
masters gpa stats programming admitted
id
22 yes 3.46 Novice Beginner 0
37 no 3.52 Novice Novice 1
35 no 3.68 Novice Beginner 1
12 no 3.65 Novice Novice 1
4 yes 3.50 Beginner Novice 1
38 yes 2.65 Advanced Beginner 1
27 yes 3.96 Advanced Advanced 0
39 yes 3.75 Advanced Beginner 0
7 yes 2.33 Novice Novice 1
40 yes 3.95 Novice Beginner 0
...
# Example 1: Export data from teradataml DataFrame into CSV,
# with only required argument.
>>> df.to_csv("export_to_csv_1.csv")
Data is successfully exported into export_to_csv_1.csv
# Example 2: Export all rows from teradataml DataFrame into CSV
# using FastExport protocol.
>>> df.to_csv("export_to_csv_2.csv", all_rows=True, fastexport=True)
Data is successfully exported into export_to_csv_2.csv
# Example 3: Export 20 rows from teradataml DataFrame into CSV.
>>> df.to_csv("export_to_csv_3.csv", num_rows=20)
Data is successfully exported into export_to_csv_3.csv
# Example 4: Export data from teradataml DataFrame into CSV using
# FastExport protocol by opening one Teradata data
# transfer session. Save errors and warnings
# thrown by fastexport.
>>> err, warn = df.to_csv("export_to_csv_4.csv", fastexport=True,
catch_errors_warnings=True, open_sessions=1 )
Data is successfully exported into export_to_csv_4.csv
>>>err
[]
>>>warn
[]
# Example 5: Export data from teradataml DataFrame into CSV
# file with '|' as field separator and single quote(')
# as field quote character.
>>> df.to_csv("export_to_csv_5.csv", sep="|", quotechar="'" )
Data is successfully exported into export_to_csv_5.csv