Separating columns of layer and exporting set of columns in a new QGIS layer

Question

I use QGIS 3.16. I need to find a way to separate the columns of a layer and export each column in a new layer named like the column.

For example: I have a file.csv that I import with the geometry wkt. After import in QGIS I have 6 columns: id, A, B, C, D and E. Is it possible to find a way to export each column in a layer .shp:

• A.shp: with 2 columns: id, A
• B.shp: id, B
• C.shp: id, C
• D.shp: id, D
• E.shp: id, E

sample of data

In this sample "id"= "MAILLE" and the columns following are A,B,C,D and E.

Do you know a way to achieve that in QGIS?

Answer 1

If its only a few and automating it is too much hassle, use Layer... Save As.. and choose a name and select the columns you want to save in the dialog:

Answer 2

The easiest way to do this all at once probably is using the algorithm from Menu Processing > Toolbox > Retain fields in batch mode:

1. Select your Input Layer, add as many rows as you want to create layers, then use Autofill... > Fill Down to insert the same layer for each row.

2. Go to the second column Fields to retain > Autofill... > Calculate by Expression and insert this expression (replace my_layer with the name of your input layer). It will automatically select the field id plus for each row another one of the remaining attribute fields:

    array( 
        array_remove_all(
            map_akeys (attributes(get_feature_by_id ('my_layer',1))),
            'id'
        )[@row_number] ,
        'id'
    )   
   

3. Select a folder/filename for the output.

You're done - when running it, you'll get 5 layers.

Answer 3

It is not QGIS solution

P.S. To me it sounds more like Pandas&GeoPandas task. Therefore try the following code:

import pandas as pd
import geopandas as gpd
from os.path import isfile, join, normpath

csv_file = 'imp2646.csv'
path_to_project = normpath('C:/Users/Taras/Downloads/project/')
path_to_csv_file = join(path_to_project, csv_file)

if isfile(path_to_csv_file):
    df = pd.read_csv(path_to_csv_file, sep=';')
    gs = gpd.GeoSeries.from_wkt(df['wkt_geom_2154'])
    gdf = gpd.GeoDataFrame(df, geometry=gs, crs="EPSG:2154")
    gdf = gdf.drop('wkt_geom_2154', axis=1)
    all_columns = gdf.columns.tolist()
    all_columns.remove('geometry')
    all_columns.remove('MAILLE')
    all_columns.sort()
    pairs = list(zip(["MAILLE"]*len(all_columns), all_columns))
    for pair in pairs:
        id, attr = pair[0], pair[1]
        attributes = list(pair)
        attributes.append('geometry')
        gdf_subset = gdf[attributes]
        gdf_subset.to_file(join(path_to_project, f"{attr}.shp"))

and get the output that will look like this:

Note: Resulting features of each layer overlap.