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I've the following code and I'm unable to drop the index and rename the seconds column. Both the index and the 2nd column have the same name "Date". How can I fix it?
Date Open High Low Last Close \
Date
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
495
Use rename_axis for change index name, if need column from index add reset_index and if necessary use 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
Or if need remove index and rename:
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
And if need only rename index name and columns name:
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
Set the index to overwrite what's there.
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
To complete your renaming
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
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