我有dataframe
。我想将一些数据转换为列表列表。我感兴趣的列是index
,Name
和Births
。我的代码有效,但似乎效率低下,并且由于某种原因,字母L被添加到每个索引的末尾。
我的代码:
import pandas as pd
data = [['Bob', 968, 'Male'], ['Jessica', 341, 'Female'], ['Mary', 77, 'Female'], ['John', 578, 'Male'], ['Mel', 434, 'Female']]
headers = ['Names', 'Births', 'Gender']
df = pd.DataFrame(data = data, columns=headers)
indexes = df.index.values.tolist()
mylist = [[x] for x in indexes]
for x in mylist:
x.extend([df.ix[x[0],'Names'], df.ix[x[0],'Births']])
print mylist
期望的输出:
[[0, 'Bob', 968], [1, 'Jessica', 341], [2, 'Mary', 77], [3, 'John', 578], [4, 'Mel', 434]]
答案 0 :(得分:4)
为什么不按照您的提及使用.values.tolist()
?
import pandas as pd
# your data
# =================================================
data = [['Bob', 968, 'Male'], ['Jessica', 341, 'Female'], ['Mary', 77, 'Female'], ['John', 578, 'Male'], ['Mel', 434, 'Female']]
headers = ['Names', 'Births', 'Gender']
df = pd.DataFrame(data = data, columns=headers)
# nested list
# ============================
df.reset_index()[['index', 'Names', 'Births']].values.tolist()
Out[46]:
[[0, 'Bob', 968],
[1, 'Jessica', 341],
[2, 'Mary', 77],
[3, 'John', 578],
[4, 'Mel', 434]]
答案 1 :(得分:1)
好的,这有效(基于李健勋的回答和评论):
import pandas as pd
# Data
data = [['Bob', 968, 'Male'], ['Jessica', 341, 'Female'], ['Mary', 77, 'Female'], ['John', 578, 'Male'], ['Mel', 434, 'Female']]
headers = ['Names', 'Births', 'Gender']
df = pd.DataFrame(data = data, columns=headers)
# Output
print df.reset_index()[['index', 'Names', 'Births']].values.astype(str).tolist()
谢谢李健勋,这也帮助了我: - )
通常,可以使用以下内容将完整的数据框转换为列表列表(这是我需要的):
df.values.astype(str).tolist()