Pandas DataFrame is a two-dimensional labeled data structure with rows and columns labels, it is looks and works similar to a table in a database or a spreadsheet. To work with the DataFrame labels, pandas provides simple tools to access and modify the rows and columns using index the ...
SASsession(prompt=False, cfgname='iom', cfgfile=config_file) def dataFrameToJmpTable(dataFrame, table): # Populate a jmp data table with a pandas dataframe # Credit: Paul Nelson cols = dataFrame.columns values = dataFrame.values for (i,k) in enumerate(cols): print(i, k, dataFrame[k]...
Since a DataFrame is a collection of Series, everything you learned in the previous lesson also applies to DataFrames. But DataFrames are two-dimensional, so indexing them is a little different. A DataFrame is conceptually like a Python dictionary…
After setting the environment variables and completing installation, your dataset can now be read into the pandas dataframe. importpandasaspdfrom.utilsimportget_client_contextfromplatform_sdk.dataset_readerimportDatasetReaderdefload(config_properties):client_context=get_client_context(config_properties)datas...
sasdata('Class', 'SASHELP', results='pandas', # dsopts={'where':'Age > 12',} ) dataFrame = sasData.to_df() values = dataFrame.values num_rows = len(values) dt = jmp.DataTable(name='Class', rows=num_rows) dataFrameToJmpTable(dataFrame, dt) 如果成功,您应该会看到打开的 Class...