CODEWITHSUNDEEP
pythonpandasnumpy
DevWebTk
DevWebTk

Reputation: 180

how add label in column for numpy array

How add label in column as string for numpy array

I need this output

   One Two Three 
A   1,  2,  3  
B   4,  5,  6  

import numpy as np
import pandas as pd
a=pd.DataFrame.from_items([('A', [1, 2, 3]), ('B', [4, 5, 6])],
orient='index', columns=['one', 'two', 'three'])
print(a)

when I use this code, the code give me the correct result, but also give me a error; that I don't understand.

Note:I dont understand this line 

a=pd.DataFrame.from_items([('A', [1, 2, 3]), ('B', [4, 5, 6])],
    orient='index', columns=['one', 'two', 'three'])

I need another method to implement this.

Output:

    one  two  three 
A    1    2      3
B    4    5      6
C:\Users\Toufik\Anaconda3\lib\site-packages\ipykernel_launcher.py:4:
FutureWarning: from_items is deprecated. Please use
DataFrame.from_dict(dict(items), ...) instead.
DataFrame.from_dict(OrderedDict(items)) may be used to preserve the
key order.   after removing the cwd from sys.path.

Upvotes: 0

Views: 10560

Answers (2)

mfitzp
mfitzp

Reputation: 15545

The warning you're being given is to tell you you're using a deprecated (to be removed) syntax. It suggests you use from_dict instead, for example

import numpy as np
import pandas as pd
a=pd.DataFrame.from_dict({
    'A': [1, 2, 3],
    'B': [4, 5, 6]
},
orient='index', columns=['one', 'two', 'three'])
print(a)

This will give your intended output

   one  two  three
A    1    2      3
B    4    5      6

Explanation

The following block which you say you don't understand —

a = pd.DataFrame.from_dict({
        'A': [1, 2, 3],
        'B': [4, 5, 6]
},
orient='index', columns=['one', 'two', 'three'])
print(a)

This creates a DataFrame from a dictionary (from_dict) which we're passing in as the first parameter. 

{'A': [1, 2, 3], 'B': [4, 5, 6]}

This dictionary has 2 entries, "A" and "B", each of which contain a list of numbers. If you pass this to pd.DataFrame.from_dict by itself, e.g.

a = pd.DataFrame.from_dict({
        'A': [1, 2, 3],
        'B': [4, 5, 6]
})
print(a)

You would get the following output.

   A  B
0  1  4
1  2  5
2  3  6

As you can see, the keys for the dictionary are being output as the column headers. To use the dictionary keys as (row) index headers and rotate the data you can pass in orient='index'.

a = pd.DataFrame.from_dict({
        'A': [1, 2, 3],
        'B': [4, 5, 6]
}, orient='index')
print(a)

This will give the following output.

   0  1  2
A  1  2  3
B  4  5  6

The final step is to pass in the column headers we want to use.

a = pd.DataFrame.from_dict({
        'A': [1, 2, 3],
        'B': [4, 5, 6]
},
orient='index', columns=['one', 'two', 'three'])
print(a)

Which gives the intended output

   one  two  three
A    1    2      3
B    4    5      6

Upvotes: 5

Vinoth96
Vinoth96

Reputation: 353

data = {'A': [1,2,3], 'B': [4,5,6]}

pd.DataFrame.from_dict(data,orient='index',columns=['one', 'two', 'three'])

Upvotes: 4

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