Latest Contributions by JamalNUMAN

Not sure what do you mean by "add the data you want to georeference to first" ... View more

In the screenshot below, using “Classify” as the primary symbology works fine. In which cases does it work, and in which does it not?   ... View more

It’s great that we can switch from one text type to another   ... View more

Thank you for the help. It works fine ... View more

Why should this be an issue? And why does it work sometimes but fail at other times? ... View more

Thank you for the input. The name of the output is generated automatically, and I don’t change it. I don’t modify the raster’s extension; it is created automatically. I’ve observed that the issue occurs even when the file path is short. Drive H is a local drive. Two observations: This issue did not exist during the ArcMap era. Sometimes, the issue disappears without making any changes at all!   ... View more

Thank you Tom for the help. The hint you provided is very useful.   I could resolve it with the help of ChatGPT, requesting the following:   Write a Python code to read the data from the table below "C:\D\T1.xlsx" Then do the following Go to the second column with the name F2, for each record, divides its values (separated by space, semicolons, or whatever) into separate columns in separate columns, then, save the result in a new table in C:\D (Name it T2) For the T2, skip the first column, then keep the first two columns, delete the next two, keep the next two, then delete the next two… repeat this pattern for all columns in T2. Save the result in T3 Now, for each row in T3, stick the values of the first column and the second column in a new record, then again stick the values of the third and the fourth column in a new record, then again stick the values of the fifth and sixth column in a new record and so forth. Save it in T4 after that, I could plot T4 in ArcGIS Pro ----------   import pandas as pd import os   # Define file paths input_file = r"C:\D\T1.xlsx" output_file_t2 = r"C:\D\T2.xlsx" output_file_t3 = r"C:\D\T3.xlsx" output_file_t4 = r"C:\D\T4.xlsx"   # Read the Excel file df = pd.read_excel(input_file)   # Check if 'F2' exists in the DataFrame if 'F2' not in df.columns:     raise ValueError("Column 'F2' not found in the input file")   # Split the values in 'F2' by common delimiters split_columns = df['F2'].astype(str).str.split(r'[; ,]+', expand=True)   # Rename columns dynamically split_columns.columns = [f'F2_part{i+1}' for i in range(split_columns.shape[1])]   # Combine with the original DataFrame (excluding the original 'F2' column) df_t2 = df.drop(columns=['F2']).join(split_columns)   # Save the new table to an Excel file df_t2.to_excel(output_file_t2, index=False) print(f"File saved successfully at: {output_file_t2}")   # Process T2 to create T3 # Skip the first column, then apply the keep-delete pattern columns_to_keep = [df_t2.columns[0]]  # Keep the first column cols = df_t2.columns[1:]  # Skip the first column   for i in range(0, len(cols), 4):     columns_to_keep.extend(cols[i:i+2])  # Keep two columns, skip two   df_t3 = df_t2[columns_to_keep]   # Save the result as T3.xlsx df_t3.to_excel(output_file_t3, index=False) print(f"File saved successfully at: {output_file_t3}")   # Process T3 to create T4 (Expanding rows based on column groups) records = [] for _, row in df_t3.iterrows():     first_col_value = row.iloc[0]  # First column value     other_values = row.iloc[1:].values  # Other column values         for i in range(0, len(other_values) - 1, 2):         if i + 1 < len(other_values):             records.append([first_col_value, other_values[i], other_values[i + 1]])   # Convert to DataFrame df_t4 = pd.DataFrame(records, columns=[df_t3.columns[0], 'Value1', 'Value2'])   # Save the result as T4.xlsx df_t4.to_excel(output_file_t4, index=False) print(f"File saved successfully at: {output_file_t4}") --------- ... View more