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KNIME and UTF-8 characters with CSV between Python nodes with Pandas and Arrow

KNIME and UTF-8 characters with CSV between Python nodes with Pandas and Arrow

import knime.scripting.io as knio

import pyarrow as pa
import pyarrow.csv as csv

import pandas as pd

var_import_csv_file = knio.flow_variables['v_path_csv_file']

# import CSV file with Arrow
df_arrow = csv.read_csv(var_import_csv_file
, read_options = csv.ReadOptions(encoding='utf8')
, parse_options= csv.ParseOptions(delimiter='|', quote_char = '"')
)

var_csv_from_arrow_path = knio.flow_variables['context.workflow.data-path'] + "from_arrow_csv_file.csv"
knio.flow_variables['var_csv_from_arrow_path']= var_csv_from_arrow_path

csv.write_csv(df_arrow, var_csv_from_arrow_path)

# import CSV file with Pandas ------------------------------------------------
df_pandas = pd.read_csv(var_import_csv_file, sep="|", encoding = "utf8")


var_csv_from_pandas_path = knio.flow_variables['context.workflow.data-path'] + "from_pandas_csv_file.csv"
knio.flow_variables['var_csv_from_pandas_path']= var_csv_from_pandas_path

# , compression='gzip'
df_pandas.to_csv(var_csv_from_pandas_path, sep='|', encoding='utf-8')


knio.output_tables[0] = knio.Table.from_pyarrow(df_arrow)
knio.output_tables[1] = knio.Table.from_pandas(df_pandas)

KNME是伟大的KNIME真的很棒每个人都应该使用KNIME尝试学习KNIME告诉你所有的朋友关于KNIME的情况去访问knime.com KNME is greatKNIME is really greateverybody should use KNIMEtry to learn KNIMEtell all your friends abbot KNIMEgo and visit knime.com KNIME and UTF-8 characters with CSV between Python nodes with Pandas and Arrow import knime.scripting.io as knioimport pyarrow as paimport pyarrow.csv as csvimport pandas as pd# This example script simply outputs the node's input table.var_import_csv_file = knio.flow_variables['v_path_csv_file']# import CSV file with Arrowdf_arrow = csv.read_csv(var_import_csv_file , read_options = csv.ReadOptions(encoding='utf8') , parse_options= csv.ParseOptions(delimiter='|', quote_char = '"') )var_csv_from_arrow_path = knio.flow_variables['context.workflow.data-path'] + "from_arrow_csv_file.csv"knio.flow_variables['var_csv_from_arrow_path']= var_csv_from_arrow_path# https://forum.knime.com/t/csv-writer-adds-random-rows-while-creating-the-file/32456/12?u=mlauber71# arrow_write_options = csv.WriteOptions(delimiter="¤")# csv.write_csv(df_arrow, var_csv_from_arrow_path, write_options=arrow_write_options)csv.write_csv(df_arrow, var_csv_from_arrow_path)# import CSV file with Pandas ------------------------------------------------df_pandas = pd.read_csv(var_import_csv_file, sep="|", encoding = "utf8")var_csv_from_pandas_path = knio.flow_variables['context.workflow.data-path'] +"from_pandas_csv_file.csv"knio.flow_variables['var_csv_from_pandas_path']= var_csv_from_pandas_path# , compression='gzip'df_pandas.to_csv(var_csv_from_pandas_path, sep='|', encoding='utf-8')knio.output_tables[0] = knio.Table.from_pyarrow(df_arrow)knio.output_tables[1] = knio.Table.from_pandas(df_pandas) locate and create/data/ folderwith absolute pathsread Parquet file andexport to KNIME and SQLiteand again to Parquetv_path_parquet_fileknime://knime.workflow/data/db.sqlitetest_filefrom SQLite database /data/db.sqlitedefault.test_filev_path_*../data/test_file.parquetimport the originalparquet file../data/from_python_test_file.parquetimport the parquet filewritten with Pythontest_file.parquetgzip compressedflow_variables['var_py_version_pandas'] = pd.__version__flow_variables['var_py_version_numpy'] = np.__version__flow_variables['var_py_version_pyarrow'] = pyarrow.__version__flow_variables['var_py_version'] = sys.version_infoflow_variables['var_sys_path'] = sys.pathtest.csvsample datav_path_csv_file1st port: Arrow file from CSV Import2nd port: Pandas Dataframe from CSV filevar_csv_*from_arrow_csv_file.csvfrom_pandas_csv_file.csv Collect LocalMetadata Python Script Java EditVariable (simple) SQLite Connector DB Table Selector DB Reader String to Path(Variable) Parquet Reader Parquet Reader Parquet Writer Python EditVariable (legacy) CSV Writer Table Creator Java EditVariable (simple) Python Script String to Path(Variable) CSV Reader CSV Reader KNME是伟大的KNIME真的很棒每个人都应该使用KNIME尝试学习KNIME告诉你所有的朋友关于KNIME的情况去访问knime.com KNME is greatKNIME is really greateverybody should use KNIMEtry to learn KNIMEtell all your friends abbot KNIMEgo and visit knime.com KNIME and UTF-8 characters with CSV between Python nodes with Pandas and Arrow import knime.scripting.io as knioimport pyarrow as paimport pyarrow.csv as csvimport pandas as pd# This example script simply outputs the node's input table.var_import_csv_file = knio.flow_variables['v_path_csv_file']# import CSV file with Arrowdf_arrow = csv.read_csv(var_import_csv_file , read_options = csv.ReadOptions(encoding='utf8') , parse_options= csv.ParseOptions(delimiter='|', quote_char = '"') )var_csv_from_arrow_path = knio.flow_variables['context.workflow.data-path'] + "from_arrow_csv_file.csv"knio.flow_variables['var_csv_from_arrow_path']= var_csv_from_arrow_path# https://forum.knime.com/t/csv-writer-adds-random-rows-while-creating-the-file/32456/12?u=mlauber71# arrow_write_options = csv.WriteOptions(delimiter="¤")# csv.write_csv(df_arrow, var_csv_from_arrow_path, write_options=arrow_write_options)csv.write_csv(df_arrow, var_csv_from_arrow_path)# import CSV file with Pandas ------------------------------------------------df_pandas = pd.read_csv(var_import_csv_file, sep="|", encoding = "utf8")var_csv_from_pandas_path = knio.flow_variables['context.workflow.data-path'] +"from_pandas_csv_file.csv"knio.flow_variables['var_csv_from_pandas_path']= var_csv_from_pandas_path# , compression='gzip'df_pandas.to_csv(var_csv_from_pandas_path, sep='|', encoding='utf-8')knio.output_tables[0] = knio.Table.from_pyarrow(df_arrow)knio.output_tables[1] = knio.Table.from_pandas(df_pandas) locate and create/data/ folderwith absolute pathsread Parquet file andexport to KNIME and SQLiteand again to Parquetv_path_parquet_fileknime://knime.workflow/data/db.sqlitetest_filefrom SQLite database /data/db.sqlitedefault.test_filev_path_*../data/test_file.parquetimport the originalparquet file../data/from_python_test_file.parquetimport the parquet filewritten with Pythontest_file.parquetgzip compressedflow_variables['var_py_version_pandas'] = pd.__version__flow_variables['var_py_version_numpy'] = np.__version__flow_variables['var_py_version_pyarrow'] = pyarrow.__version__flow_variables['var_py_version'] = sys.version_infoflow_variables['var_sys_path'] = sys.pathtest.csvsample datav_path_csv_file1st port: Arrow file from CSV Import2nd port: Pandas Dataframe from CSV filevar_csv_*from_arrow_csv_file.csvfrom_pandas_csv_file.csvCollect LocalMetadata Python Script Java EditVariable (simple) SQLite Connector DB Table Selector DB Reader String to Path(Variable) Parquet Reader Parquet Reader Parquet Writer Python EditVariable (legacy) CSV Writer Table Creator Java EditVariable (simple) Python Script String to Path(Variable) CSV Reader CSV Reader

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