尝试：

tmp = {vv: k for k, v in categories.items() for vv in v}

x = df.explode("col1")

x["col2"] = x["col1"].apply(
    lambda x: "{}-{}".format(tmp[x], x) if x in tmp else np.nan
)

x = x.groupby(level=0).agg(
    col1=("col1", list), col2=("col2", lambda x: ", ".join(x[x.notna()]))
)
print(x)

印刷品：

col1             col2
0                     [plane, chair]  transport-plane
1  [computer, beach, book, language]     reading-book
2                [rice, bus, street]        food-rice

怎么样：

import pandas as pd

df = pd.DataFrame([{'col1': ['plane', 'chair']}, {'col1': ['computer', 'beach', 'book', 'language']}, {'col1': ['rice', 'bus', 'street']}])

categories = {
    'transport': ['car', 'truck', 'plane'],
    'reading': ['book', 'library'],
    'food': ['rice', 'milk', 'tea']
}

def match_pairs(categories, df):
  col2=[]
  index=0
  for v in categories:
    print(f'{df["col1"][index]} at index {index}')
    for entry in df['col1'][index]:
      print(f"Finding [{entry}] in {categories[v]}...")
      if entry in categories[v]:
        col2.append(v+'-'+entry)
        break
    index += 1
  print(col2)
  df['col2'] = col2
  return df

print (match_pairs(categories, df))