Extract first and last row of a dataframe in pandas

Question

How can I extract the first and last rows of a given dataframe as a new dataframe in pandas?

I've tried to use iloc to select the desired rows and then concat as in:

df=pd.DataFrame({'a':range(1,5), 'b':['a','b','c','d']})
pd.concat([df.iloc[0,:], df.iloc[-1,:]])

but this does not produce a pandas dataframe:

a    1
b    a
a    4
b    d
dtype: object

xXx · Accepted Answer · 2021-07-13 00:45:45Z

224

I think the most simple way is .iloc[[0, -1]].

df = pd.DataFrame({'a':range(1,5), 'b':['a','b','c','d']})
df2 = df.iloc[[0, -1]]
    
print(df2)

   a  b
0  1  a
3  4  d

edited Jul 13, 2021 at 0:45

xXx

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answered Apr 11, 2016 at 7:23

su79eu7k

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2 Comments

joh-mue Over a year ago

mind that this duplicates the first row if the frame only contains a single row

mirekphd Over a year ago

note that iloc is required for df when using last element index (-1), which makes it different from lists and non-last indices

Colonel Beauvel · Accepted Answer · 2016-04-11 07:34:27Z

122

You can also use head and tail:

In [29]: pd.concat([df.head(1), df.tail(1)])
Out[29]:
   a  b
0  1  a
3  4  d

answered Apr 11, 2016 at 7:34

Colonel Beauvel

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1 Comment

Seth Over a year ago

I think this is the best solution as it applies to everything. I was getting "index position out of bounds" errors when trying to use .iloc on slices of a frame (which makes sense as the index changes) did not want to reset_index as the current index was important

Bryan P · Accepted Answer · 2023-09-11 20:39:47Z

23

Some of the other answers duplicate the first row if the frame only contains a single row. If that's a concern

df[0::len(df)-1 if len(df) > 1 else 1]

works even for single row-dataframes.

Example: For the following dataframe this will not create a duplicate:

df = pd.DataFrame({'a': [1], 'b':['a']})
df2 = df[0::len(df)-1 if len(df) > 1  else 1]

print df2

   a  b
0  1  a

whereas this does:

df3 = df.iloc[[0, -1]]

print df3 

   a  b
0  1  a
0  1  a

because the single row is the first AND last row at the same time.

edited Sep 11, 2023 at 20:39

Bryan P

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answered Dec 18, 2018 at 16:32

joh-mue

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1 Comment

Bryan P Over a year ago

Good point. Can you provide an example output to make a more complete answer

jezrael · Accepted Answer · 2016-04-11 07:23:17Z

8

I think you can try add parameter axis=1 to concat, because output of df.iloc[0,:] and df.iloc[-1,:] are Series and transpose by T:

print df.iloc[0,:]
a    1
b    a
Name: 0, dtype: object

print df.iloc[-1,:]
a    4
b    d
Name: 3, dtype: object

print pd.concat([df.iloc[0,:], df.iloc[-1,:]], axis=1)
   0  3
a  1  4
b  a  d

print pd.concat([df.iloc[0,:], df.iloc[-1,:]], axis=1).T
   a  b
0  1  a
3  4  d

edited Apr 11, 2016 at 7:23

answered Apr 11, 2016 at 7:18

jezrael

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Comments

rachwa · Accepted Answer · 2022-06-11 19:34:29Z

5

Alternatively you can use take:

In [3]: df.take([0, -1])
Out[3]: 
   a  b
0  1  a
3  4  d

answered Jun 11, 2022 at 19:34

rachwa

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Comments

Mina Gabriel · Accepted Answer · 2020-05-05 14:36:52Z

1

Here is the same style as in large datasets:

x = df[:5]
y = pd.DataFrame([['...']*df.shape[1]], columns=df.columns, index=['...'])
z = df[-5:]
frame = [x, y, z]
result = pd.concat(frame)

print(result)

Output:

                     date  temp
0     1981-01-01 00:00:00  20.7
1     1981-01-02 00:00:00  17.9
2     1981-01-03 00:00:00  18.8
3     1981-01-04 00:00:00  14.6
4     1981-01-05 00:00:00  15.8
...                   ...   ...
3645  1990-12-27 00:00:00    14
3646  1990-12-28 00:00:00  13.6
3647  1990-12-29 00:00:00  13.5
3648  1990-12-30 00:00:00  15.7
3649  1990-12-31 00:00:00    13

answered May 5, 2020 at 14:36

Mina Gabriel

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1 Comment

Bryan P Over a year ago

Nice... although it does have the same type of duplication challenge for lists with <10 elements. Seems you might need to wrap things in an if statement to get things to work for shorter dataframes.

Kenneth Ng · Accepted Answer · 2024-11-27 05:33:32Z

0

I think simply just:

df2 = df[-1:]

then could extract the last role to save in df2

answered Nov 27, 2024 at 5:33

Kenneth Ng

1

2 Comments

Community Over a year ago

Your answer could be improved with additional supporting information. Please edit to add further details, such as citations or documentation, so that others can confirm that your answer is correct. You can find more information on how to write good answers in the help center.

sondra.kinsey Over a year ago

The OP asked to have the first and last joined a new dataframe as the result. This doesn't include the first at all.

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