将元组列表转换为 DataFrame(第一个参数:列,第二个参数:值)
Converting a list of list of tuples to a DataFrame (First argument: column, Second argument: value)
所以我需要一个来自 list_of_list_of_tuples:
的 DataFrame
我的数据是这样的:
元组 = [[(5,0.45),(6,0.56)],[(1,0.23),(2,0.54),(6,0.63)],[(3,0.86),( 6,0.36)]]
我需要的是这个:
index
1
2
3
4
5
6
1
nan
nan
nan
nan
0.45
0.56
2
0.23
0.54
nan
nan
nan
0.63
3
nan
nan
0.86
nan
nan
0.36
所以元组中的第一个参数是列,第二个是值。
索引也很好。
谁能帮我?
我不知道如何制定代码。
将每个元组转换为字典,传递给 DataFrame
构造函数并最后添加 DataFrame.reindex
以更改顺序并添加缺失的列:
df = pd.DataFrame([dict(x) for x in tuples])
df = df.reindex(range(df.columns.min(), df.columns.max() + 1), axis=1)
print (df)
1 2 3 4 5 6
0 NaN NaN NaN NaN 0.45 0.56
1 0.23 0.54 NaN NaN NaN 0.63
2 NaN NaN 0.86 NaN NaN 0.36
tuples = [[(5,0.45),(6,0.56)],[(1,0.23),(2,0.54),(6,0.63)],[(3,0.86),(6,0.36)]]
for x in tuples:
print(x)
index=[]
values=[]
for tuple in x:
print(tuple[0],tuple[1])
index.append(tuple[0])
values.append(tuple[1])
print(index,values)
所以我需要一个来自 list_of_list_of_tuples:
的 DataFrame我的数据是这样的:
元组 = [[(5,0.45),(6,0.56)],[(1,0.23),(2,0.54),(6,0.63)],[(3,0.86),( 6,0.36)]]
我需要的是这个:
index | 1 | 2 | 3 | 4 | 5 | 6 |
---|---|---|---|---|---|---|
1 | nan | nan | nan | nan | 0.45 | 0.56 |
2 | 0.23 | 0.54 | nan | nan | nan | 0.63 |
3 | nan | nan | 0.86 | nan | nan | 0.36 |
所以元组中的第一个参数是列,第二个是值。 索引也很好。 谁能帮我? 我不知道如何制定代码。
将每个元组转换为字典,传递给 DataFrame
构造函数并最后添加 DataFrame.reindex
以更改顺序并添加缺失的列:
df = pd.DataFrame([dict(x) for x in tuples])
df = df.reindex(range(df.columns.min(), df.columns.max() + 1), axis=1)
print (df)
1 2 3 4 5 6
0 NaN NaN NaN NaN 0.45 0.56
1 0.23 0.54 NaN NaN NaN 0.63
2 NaN NaN 0.86 NaN NaN 0.36
tuples = [[(5,0.45),(6,0.56)],[(1,0.23),(2,0.54),(6,0.63)],[(3,0.86),(6,0.36)]]
for x in tuples:
print(x)
index=[]
values=[]
for tuple in x:
print(tuple[0],tuple[1])
index.append(tuple[0])
values.append(tuple[1])
print(index,values)