我有不同列中的数据,但我不知道如何提取它以将其保存在另一个变量中.
index a b c
1 2 3 4
2 3 4 5
我该如何选择'a','b'并保存到DF1？
我试过了
df1 = df['a':'b']
df1 = df.ix[:, 'a':'b']
似乎没有工作.
我有以下名为'data.csv'的文件:
1997,Ford,E350
1997, Ford , E350
1997,Ford,E350,"Super, luxurious truck"
1997,Ford,E350,"Super ""luxurious"" truck"
1997,Ford,E350," Super luxurious truck "
"1997",Ford,E350
1997,Ford,E350
2000,Mercury,Cougar
我想将它解析为pandas DataFrame,以便DataFrame如下所示:
Year Make Model Description
0 1997 Ford E350 None
1 1997 Ford E350 None
2 1997 Ford E350 Super, luxurious truck
3 1997 Ford E350 Super "luxurious" truck
4 1997 Ford E350 Super luxurious truck
5 1997 Ford E350 None
6 1997 Ford E350 None
7 2000 Mercury Cougar None
我能做的最好的事情是:
pd.read_table("data.csv", sep=r',', names=["Year", "Make", "Model", "Description"])
哪个让我: …
我试图从我拥有的数据框中删除空格.列名称如下所示.我试图获取名称之间的空格,并将其替换为"_",无论何时出现.
['join_date' 'fiscal_quarter' 'fiscal_year' 'primary_channel'
'secondary_channel' 'customer_count' 'new_members' 'revisit_next_day'
'revisit_14_day' 'demand_1yr' 'revisit_next_day_rate'
'revisit_14_day_rate' 'demand_1yr_per_new_member' u'ch_Ad Network'
u'ch_Affiliate' u'ch_Branded SEM' u'ch_DSP' u'ch_Daily Email'
u'ch_Daily Messaging' u'ch_Direct' u'ch_Direct Publisher' u'ch_Email'
u'ch_Feeds' u'ch_Native' u'ch_Non-Branded SEM' u'ch_Organic Search'
u'ch_Paid Social' u'ch_Site' u'ch_Special Email' u'ch_Television'
u'ch_Trigger Email' u'ch_UNMAPPED' u'ch_Unpaid Social' u'quarter_Q2'
u'quarter_Q3' u'quarter_Q4']