從2D字典中，如何將其轉換為數據框或存在/不存在的矩陣，其中列表中的值是列，鍵是行名？我將目標列表中的值累加到一個矩陣中。我一直在嘗試，但是沒有成功：values = set()for genome, info in dict_cluster.items(): for v in info: #t = [genome, ([v for v in info])] t = [genome,v] print pd.DataFrame(t)輸入：A ['arylpolyene', 'hserlactone', 'hserlactone', 'nrps', 'siderophore', 't1pks-nrps', 'terpene', 'thiopeptide', 'transatpks-nrps']B ['hserlactone', 'hserlactone-arylpolyene', 'nrps', 'siderophore', 'thiopeptide']C ['nrps', 'nrps', 'nrps', 'siderophore', 't1pks-nrps', 't1pks-nrps']D ['nrps', 'siderophore', 't1pks-nrps']輸出： arylpolyene siderophore hserlactone-arylpolyene transatpks-nrps terpene thiopeptide hserlactone nrps t1pks-nrpsA 1 2 0 1 1 1 2 1 1B 0 1 1 0 0 1 1 1 0C 0 1 0 0 0 0 0 3 2D 0 1 0 0 0 0 0 1 1我的輸出是這樣的： 00 GCF_900068895.11 transatpks-nrps 00 GCA_002415165.11 thiopeptide 00 GCA_000367685.21 t1pks-nrps 00 GCA_002732135.11 t1pks-nrps
3 回答
吃雞游戲
TA貢獻1829條經驗 獲得超7個贊
也許您正在尋找這樣的東西：
val = {'A': ['arylpolyene', 'hserlactone', 'hserlactone', 'nrps', 'siderophore', 't1pks-nrps', 'terpene', 'thiopeptide', 'transatpks-nrps'],
'B': ['hserlactone', 'hserlactone-arylpolyene', 'nrps', 'siderophore', 'thiopeptide'],
'C': ['nrps', 'nrps', 'nrps', 'siderophore', 't1pks-nrps', 't1pks-nrps'],
'D': ['nrps', 'siderophore', 't1pks-nrps']}
all_val = []
for k in val:
for v in val[k]:
all_val.append((k,v))
df = pd.DataFrame(all_val,columns=['key','val']).set_index('key')
df_count = df.pivot_table(index='key',columns='val',aggfunc=len)
輸出：
val arylpolyene hserlactone hserlactone-arylpolyene nrps siderophore \
key
A 1.0 2.0 NaN 1.0 1.0
B NaN 1.0 1.0 1.0 1.0
C NaN NaN NaN 3.0 1.0
D NaN NaN NaN 1.0 1.0
val t1pks-nrps terpene thiopeptide transatpks-nrps
key
A 1.0 1.0 1.0 1.0
B NaN NaN 1.0 NaN
C 2.0 NaN NaN NaN
D 1.0 NaN NaN NaN
侃侃無極
TA貢獻2051條經驗 獲得超10個贊
這應該可以完成您的工作（我正在使用Python3）：
my_dict = {
'A': ['arylpolyene', 'hserlactone', 'hserlactone', 'nrps', 'siderophore', 't1pks-nrps', 'terpene', 'thiopeptide', 'transatpks-nrps'],
'B': ['hserlactone', 'hserlactone-arylpolyene', 'nrps', 'siderophore', 'thiopeptide'],
'C': ['nrps', 'nrps', 'nrps', 'siderophore', 't1pks-nrps', 't1pks-nrps'],
'D': ['nrps', 'siderophore', 't1pks-nrps']
}
rows_list=list(my_dict.keys())
values=list(my_dict.values())
rows_size=len(rows_list)
columns_list = []
for sublist in values:
for item in sublist:
if item not in columns_list:
columns_list.append(item)
columns_size = len(columns_list)
#initialize adjacent matrix
print('Initial adjacent matrix')
adjacent = [ [0]*columns_size for i in range(rows_size) ]
for row in adjacent:
print(row)
for key, value in my_dict.items():
for v in value:
adjacent[rows_list.index(key)][columns_list.index(v)] += 1
print('-'*50)
print('Final adjacent matrix')
for row in adjacent:
print(row)
在第一個循環中，for sublist in values:我創建一個列表，其中包含您想要的值作為沒有重復項的列。
在“adjacent = [ [0]*columns_size for i in range(rows_size) ]我創建的列表”中，元素與字典鍵的數量一樣多。每個元素都是一個列表，其中元素的數量與列值的數量一樣多。
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