You need to have an instance of the DeltaTable class, but you're passing the DataFrame instead. For this you need to create it using the DeltaTable.forPath (pointing to a specific path) or DeltaTable.forName (for a named table), like this:

DEV_Delta = DeltaTable.forPath(spark, 'some path')
DEV_Delta.alias("t").merge(df_from_pbl.alias("s"),condition_dev)\
  .whenMatchedUpdateAll() \
  .whenNotMatchedInsertAll()\
  .execute()

If you have data as DataFrame only, you need to write them first.

See documentation for more details.

Note that merge is a method of DataFrame, not Series.

So change your code to:

application_prev_data = application_data.to_frame().merge(...)

(first convert your Series to a DataFrame (with a single column) and then merge).

"sklearn.datasets" is a scikit package, where it contains a method load_iris().

load_iris(), by default return an object which holds data, target and other members in it. In order to get actual values you have to read the data and target content itself.

Whereas 'iris.csv', holds feature and target together.

FYI: If you set return_X_y as True in load_iris(), then you will directly get features and target.

from sklearn import datasets
data,target = datasets.load_iris(return_X_y=True)

You need change exp as column name for rename:

def merge_files(files, **kwargs):
    dfs = []
    for f in files:
        dfs.append(
            pd.read_csv(f, sep='\t', usecols=['r_id', 'exp'], index_col=['r_id'])
              .rename(columns={'exp':os.path.splitext(os.path.basename(f))[0]})
        )
    return pd.concat(dfs, axis=1)

result = merge_files(files).reset_index()
print(result)
  r_id  test1  test2  test3
0   r1     20     20     30
1   r2     30     30     40
2   r3      1      1     11
3   r4      3      3     32

That way of merging is creating a Pandas DataFrame. Try this:

import geopandas as gpd

df = gpd.read_file(r"/home/bera/Drives/data1/data/LMV/LMV-data_2021-10/ok_riks_Sweref_99_TM_shape/oversikt/riks/ak_riks.shp")

gdf1 = df.head(10)
gdf2 = df.tail(10)

print(type(gdf1.merge(gdf2, on="LANSKOD", how="outer"))) #This is creating a pandas df
#pandas.core.frame.DataFrame

merged = gpd.pd.merge(gdf1, gdf2, on="LANSKOD", how="outer")
print(type(merged))
#<class 'geopandas.geodataframe.GeoDataFrame'> #Now it is a geopandas df

merged["geometry"] = merged["geometry_x"].combine_first(merged["geometry_y"]) #Create a complete geometry column
merged = merged.drop(columns=["geometry_x", "geometry_y"])
merged.to_file(r"/home/bera/Desktop/GIStest/testmerge.shp")