我有以下代码，我无法删除索引并重命名秒列。索引和第二列都具有相同的名称＆＃34; GHCi> fmap ($ 3) ((4 :: Integer)+)
<interactive>:42:13: error:
* Couldn't match type `Integer' with `Integer -> b'
Expected type: Integer -> Integer -> b
Actual type: Integer -> Integer
* In the second argument of `fmap', namely `((4 :: Integer) +)'
In the expression: fmap ($ 3) ((4 :: Integer) +)
In an equation for `it': it = fmap ($ 3) ((4 :: Integer) +)
* Relevant bindings include
it :: Integer -> b (bound at <interactive>:42:1)
＆＃34;。我该如何解决？
Date答案 0 :(得分：3)
使用rename_axis表示更改索引名称，如果需要index列添加reset_index，必要时使用rename：
df = df.rename_axis('Date1').reset_index().rename(columns={'Date':'New'})
print (df)
Date1 New Open High Low Last Close
0 2010-12-31 2010-12-31 71.50 74.00 71.50 72.05 72.40
1 2011-01-31 2011-01-31 70.05 73.00 70.05 72.70 72.75
2 2011-02-28 2011-02-28 77.00 77.00 74.80 74.90 74.85
3 2011-03-31 2011-03-31 54.35 58.85 54.35 55.00 55.25
4 2011-04-30 2011-04-29 60.50 60.50 58.10 58.10 58.20
5 2011-05-31 2011-05-31 52.50 53.50 52.10 52.95 52.55
6 2011-06-30 2011-06-30 46.30 46.95 45.60 46.60 46.65
7 2011-07-31 2011-07-29 49.70 50.40 49.30 49.30 49.60
8 2011-08-31 2011-08-30 45.10 47.90 43.05 47.85 47.45
9 2011-09-30 2011-09-30 42.05 43.45 41.40 41.75 41.85
10 2011-10-31 2011-10-31 43.70 43.70 41.10 43.70 43.70
11 2011-11-30 2011-11-30 39.95 39.95 38.05 38.15 38.15
12 2011-12-31 2011-12-30 31.55 35.80 31.15 34.00 34.10
13 2012-01-31 2012-01-31 44.95 45.30 43.70 44.00 44.00
14 2012-02-29 2012-02-29 47.90 49.00 46.15 47.00 46.25
15 2012-03-31 2012-03-30 44.75 44.75 43.60 44.40 44.45
16 2012-04-30 2012-04-30 70.00 75.60 66.70 75.60 75.60
或者如果需要删除索引并重命名：
df = df.reset_index(drop=True).rename(columns={'Date':'New'})
print (df)
New Open High Low Last Close
0 2010-12-31 71.50 74.00 71.50 72.05 72.40
1 2011-01-31 70.05 73.00 70.05 72.70 72.75
2 2011-02-28 77.00 77.00 74.80 74.90 74.85
3 2011-03-31 54.35 58.85 54.35 55.00 55.25
4 2011-04-29 60.50 60.50 58.10 58.10 58.20
5 2011-05-31 52.50 53.50 52.10 52.95 52.55
6 2011-06-30 46.30 46.95 45.60 46.60 46.65
7 2011-07-29 49.70 50.40 49.30 49.30 49.60
8 2011-08-30 45.10 47.90 43.05 47.85 47.45
9 2011-09-30 42.05 43.45 41.40 41.75 41.85
10 2011-10-31 43.70 43.70 41.10 43.70 43.70
11 2011-11-30 39.95 39.95 38.05 38.15 38.15
12 2011-12-30 31.55 35.80 31.15 34.00 34.10
13 2012-01-31 44.95 45.30 43.70 44.00 44.00
14 2012-02-29 47.90 49.00 46.15 47.00 46.25
15 2012-03-30 44.75 44.75 43.60 44.40 44.45
16 2012-04-30 70.00 75.60 66.70 75.60 75.60
如果只需要重命名索引名称和列名称：
df = df.rename_axis('Date1').rename(columns={'Date':'New'})
print (df)
New Open High Low Last Close
Date1
2010-12-31 2010-12-31 71.50 74.00 71.50 72.05 72.40
2011-01-31 2011-01-31 70.05 73.00 70.05 72.70 72.75
2011-02-28 2011-02-28 77.00 77.00 74.80 74.90 74.85
2011-03-31 2011-03-31 54.35 58.85 54.35 55.00 55.25
2011-04-30 2011-04-29 60.50 60.50 58.10 58.10 58.20
2011-05-31 2011-05-31 52.50 53.50 52.10 52.95 52.55
2011-06-30 2011-06-30 46.30 46.95 45.60 46.60 46.65
2011-07-31 2011-07-29 49.70 50.40 49.30 49.30 49.60
2011-08-31 2011-08-30 45.10 47.90 43.05 47.85 47.45
2011-09-30 2011-09-30 42.05 43.45 41.40 41.75 41.85
2011-10-31 2011-10-31 43.70 43.70 41.10 43.70 43.70
2011-11-30 2011-11-30 39.95 39.95 38.05 38.15 38.15
2011-12-31 2011-12-30 31.55 35.80 31.15 34.00 34.10
2012-01-31 2012-01-31 44.95 45.30 43.70 44.00 44.00
2012-02-29 2012-02-29 47.90 49.00 46.15 47.00 46.25
2012-03-31 2012-03-30 44.75 44.75 43.60 44.40 44.45
2012-04-30 2012-04-30 70.00 75.60 66.70 75.60 75.60
答案 1 :(得分：2)
设置索引以覆盖那里的内容。
df.set_index('Date')
Open High Low Last Close
Date
2010-12-31 71.50 74.00 71.50 72.05 72.40
2011-01-31 70.05 73.00 70.05 72.70 72.75
2011-02-28 77.00 77.00 74.80 74.90 74.85
2011-03-31 54.35 58.85 54.35 55.00 55.25
2011-04-29 60.50 60.50 58.10 58.10 58.20
2011-05-31 52.50 53.50 52.10 52.95 52.55
2011-06-30 46.30 46.95 45.60 46.60 46.65
2011-07-29 49.70 50.40 49.30 49.30 49.60
2011-08-30 45.10 47.90 43.05 47.85 47.45
2011-09-30 42.05 43.45 41.40 41.75 41.85
2011-10-31 43.70 43.70 41.10 43.70 43.70
2011-11-30 39.95 39.95 38.05 38.15 38.15
2011-12-30 31.55 35.80 31.15 34.00 34.10
2012-01-31 44.95 45.30 43.70 44.00 44.00
2012-02-29 47.90 49.00 46.15 47.00 46.25
2012-03-30 44.75 44.75 43.60 44.40 44.45
2012-04-30 70.00 75.60 66.70 75.60 75.60
完成重命名
df.set_index('Date').rename_axis('SomeName').reset_index()
SomeName Open High Low Last Close
0 2010-12-31 71.50 74.00 71.50 72.05 72.40
1 2011-01-31 70.05 73.00 70.05 72.70 72.75
2 2011-02-28 77.00 77.00 74.80 74.90 74.85
3 2011-03-31 54.35 58.85 54.35 55.00 55.25
4 2011-04-29 60.50 60.50 58.10 58.10 58.20
5 2011-05-31 52.50 53.50 52.10 52.95 52.55
6 2011-06-30 46.30 46.95 45.60 46.60 46.65
7 2011-07-29 49.70 50.40 49.30 49.30 49.60
8 2011-08-30 45.10 47.90 43.05 47.85 47.45
9 2011-09-30 42.05 43.45 41.40 41.75 41.85
10 2011-10-31 43.70 43.70 41.10 43.70 43.70
11 2011-11-30 39.95 39.95 38.05 38.15 38.15
12 2011-12-30 31.55 35.80 31.15 34.00 34.10
13 2012-01-31 44.95 45.30 43.70 44.00 44.00
14 2012-02-29 47.90 49.00 46.15 47.00 46.25
15 2012-03-30 44.75 44.75 43.60 44.40 44.45
16 2012-04-30 70.00 75.60 66.70 75.60 75.60
答案 2 :(得分：2)
使用rename_axis，您有不同的名称，可以添加reset_index()
df.rename_axis('Yourname')
或
df.index.name='Yourname'
答案 3 :(得分：1)
尝试使用重置索引：
df.reset_index(drop = True)