3 回答

TA貢獻(xiàn)1773條經(jīng)驗 獲得超3個贊
當(dāng)您將Pandas DataFrame列拉出時,它們就是Pandas Series,然后您可以調(diào)用x.tolist()它們以將其轉(zhuǎn)換為Python列表?;蛘?,您也可以使用list(x)。
import pandas as pd
d = {'one' : pd.Series([1., 2., 3.], index=['a', 'b', 'c']),
'two' : pd.Series([1., 2., 3., 4.], index=['a', 'b', 'c', 'd'])}
df = pd.DataFrame(d)
print("Starting with this dataframe\n", df)
print("The first column is a", type(df['one']), "\nconsisting of\n", df['one'])
dfToList = df['one'].tolist()
dfList = list(df['one'])
dfValues = df['one'].values
print("dfToList is", dfToList, "and it's a", type(dfToList))
print("dfList is ", dfList, "and it's a", type(dfList))
print("dfValues is", dfValues, "and it's a", type(dfValues))
最后幾行返回:
dfToList is [1.0, 2.0, 3.0, nan] and it's a <class 'list'>
dfList is [1.0, 2.0, 3.0, nan] and it's a <class 'list'>
dfValues is [ 1. 2. 3. nan] and it's a <class 'numpy.ndarray'>
這個問題可能會有所幫助。一旦您了解了Pandas的風(fēng)格,它們實際上就是相當(dāng)不錯的。
因此,您可以:
my_list = df["cluster"].tolist()
然后從那里去。

TA貢獻(xiàn)1785條經(jīng)驗 獲得超8個贊
這將返回一個numpy數(shù)組:
my_list = df["cluster"].values
這將返回一個numpy數(shù)組,用于唯一值:
my_list = df["cluster"].values
uniqueVals = np.unique(my_list)
或者:
uniqueVals = df["cluster"].unique()

TA貢獻(xiàn)1829條經(jīng)驗 獲得超7個贊
轉(zhuǎn)換示例:
numpy數(shù)組->熊貓數(shù)據(jù)框->熊貓列中的列表
numpy數(shù)組
data = np.array([[10,20,30], [20,30,60], [30,60,90]])
將numpy數(shù)組轉(zhuǎn)換為熊貓框架
data = np.array([[10,20,30], [20,30,60], [30,60,90]])
dataPd = pd.DataFrame(data = data)
print(dataPd)
0 1 2
0 10 20 30
1 20 30 60
2 30 60 90
轉(zhuǎn)換一個熊貓框到列表
pdToList = list(dataPd['2'])
遍歷列表作為證明
for counter, value in enumerate(pdToList):
print(counter, value)
0 90
1 60
2 30
添加回答
舉報