[英]Groupby to convert Pandas DataFrame to list of dictionaries
我有以下 DataFrame:
print(df)
business_id software_id quantity price inventory_level
1234 abc 10 25.5 5
4820 bce 40 21.9 2
1492 abc 59 25.3 1
1234 abc 55 11.3 0
我想创建一个字典列表,保留列名并存储不是键的内容 - 这里是“business_id”和“software_id” - 作为字典列表,使用 Pandas 的 groupby 并因此获得:
[
{
business_id: 1234,
software_id: abc,
transactions: [
{quantity: 10, price: 25.5, inventory_level:5},
{quantity: 55, price: 11.3, inventory_level:0},
]}
(...)
]
低效的版本是:
keys_l = ["business_id", "software_id"]
keys_df = df.filter(keys_l).drop_duplicates()
chunk_l = []
for _, row in keys_df.iterrows():
# --- Subset original DataFrame ---
chunk_df = df[(df[keys_l]==row).all(axis=1)]
# --- Create baseline keys with keys ---
chunk_dict = {key: value for key, value in zip(row.index, row.values)}
# --- Add bucketed data points ---
chunk_dict["transactions"] = chunk_df.drop(keys_l, axis=1).to_dict(orient="records")
# --- Append to list to create a list of dictionaries ---
chunk_l.append(chunk_dict)
如何通过 Pandas'groupby 获得相同的结果?
你能试试这个吗:
dfx=df.groupby(['business_id','software_id']).agg(list).T
final=[]
for i in dfx.columns:
final.append({'business_id':i[0], 'software_id':i[1],
'transactions':[{'quantity':dfx[i]['quantity'][j],'price':dfx[i]['price'][j],'inventory_level':dfx[i]['inventory_level'][j]} for j in range(len(dfx[i][0]))]})
print(final)
'''
[
{'business_id': 1234, 'software_id': 'abc', 'transactions': [{'quantity': 10, 'price': 25.5, 'inventory_level': 5}, {'quantity': 55, 'price': 11.3, 'inventory_level': 0}]},
{'business_id': 1492, 'software_id': 'abc', 'transactions': [{'quantity': 59, 'price': 25.3, 'inventory_level': 1}]},
{'business_id': 4820, 'software_id': 'bce', 'transactions': [{'quantity': 40, 'price': 21.9, 'inventory_level': 2}]}
]
'''
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