CODEWITHSUNDEEP
pythonpandas
Dan
Dan

Reputation: 12675

How can I print out just the index of a pandas dataframe?

I'm trying to make a table, and the way Pandas formats its indices is exactly what I'm looking for. That said, I don't want the actual data, and I can't figure out how to get Pandas to print out just the indices without the corresponding data.

Upvotes: 48

Views: 278810

Answers (5)

user716255
user716255

Reputation: 453

You can always try df.index. This function will show you the range index.

Or you can always set your index. Let say you had a weather.csv file with headers: 'date', 'temperature' and 'event'. And you want set "date" as your index.

import pandas as pd 
df = pd.read_csvte'weather_file)
df.set_index('day', inplace=True)
df

Upvotes: 0

Akshat
Akshat

Reputation: 11

You can use lamba function:

index = df.index[lambda x : for x in df.index() ]
print(index)

Upvotes: 1

NILESH KUMAR P.HD
NILESH KUMAR P.HD

Reputation: 432

You can access the index attribute of a df using df.index[i]

>> import pandas as pd
>> import numpy as np
>> df = pd.DataFrame({'a':np.arange(5), 'b':np.random.randn(5)})
   a         b
0  0  1.088998
1  1 -1.381735
2  2  0.035058
3  3 -2.273023
4  4  1.345342

>> df.index[1] ## Second index
>> df.index[-1] ## Last index

>> for i in xrange(len(df)):print df.index[i] ## Using loop
... 
0
1
2
3
4

Upvotes: 11

fixxxer
fixxxer

Reputation: 16154

.index.tolist() is another function which you can get the index as a list:

In [1391]: datasheet.head(20).index.tolist()
Out[1391]: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19]

Upvotes: 32

EdChum
EdChum

Reputation: 394129

You can access the index attribute of a df using .index:

In [277]:

df = pd.DataFrame({'a':np.arange(10), 'b':np.random.randn(10)})
df
Out[277]:
   a         b
0  0  0.293422
1  1 -1.631018
2  2  0.065344
3  3 -0.417926
4  4  1.925325
5  5  0.167545
6  6 -0.988941
7  7 -0.277446
8  8  1.426912
9  9 -0.114189
In [278]:

df.index
Out[278]:
Int64Index([0, 1, 2, 3, 4, 5, 6, 7, 8, 9], dtype='int64')

Upvotes: 66

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