CODEWITHSUNDEEP
pythonpandas
ds_enth
ds_enth

Reputation: 59

How to transform a single column dataframe to a single row dataframe in Pandas?

I got the following dataframe:

                        0
0                  Aachen
1                       1
2                   Valid
3                      L5
4                      21
5                    Fell
6  01/01/1880 12:00:00 AM
7                  50.775
8                 6.08333
9   (50.775000, 6.083330)

And I want it to look like:

name    id  nametype    recclass    mass (g)    fall    year    reclat  reclong GeoLocation
Aachen  1   Valid   L5  21  Fell    1-1-1880 12:00:00 AM    50.775000   6.083330    (50.775000, 6.083330)

I tried using pivot() an pivot_table() in pandas, but I always get a KeyError:

pv_df = df.pivot_table(index=None, columns='0')

Traceback (most recent call last):
  File "/home/alaaeddine/PycharmProjects/test/expectations.py", line 18, in <module>
    pv_df = df.pivot_table(index=None, columns='0')
  File "/usr/local/lib/python3.6/dist-packages/pandas/core/frame.py", line 5303, in pivot_table
    margins_name=margins_name)
  File "/usr/local/lib/python3.6/dist-packages/pandas/core/reshape/pivot.py", line 86, in pivot_table
    grouped = data.groupby(keys, observed=False)
  File "/usr/local/lib/python3.6/dist-packages/pandas/core/generic.py", line 6665, in groupby
    observed=observed, **kwargs)
  File "/usr/local/lib/python3.6/dist-packages/pandas/core/groupby/groupby.py", line 2152, in groupby
    return klass(obj, by, **kwds)
  File "/usr/local/lib/python3.6/dist-packages/pandas/core/groupby/groupby.py", line 599, in __init__
    mutated=self.mutated)
  File "/usr/local/lib/python3.6/dist-packages/pandas/core/groupby/groupby.py", line 3291, in _get_grouper
    raise KeyError(gpr)
KeyError: '0'

Also tried to set the index and stack/unstack but it does not seem to work.

Any clues on what I am might be missing/doing worng?

Thanks!

Upvotes: 1

Views: 8048

Answers (4)

ds_enth
ds_enth

Reputation: 59

Thanks for your help guys, I could make work using the following code:

import pandas as pd

#create the dataset
dt = pd.read_csv('/path/to/file.csv')

# extract the first row in a new dataframe
df = pd.DataFrame(dt.values[0])

# transpose the new dataframe
df = df.transpose()

# rename the columns of the new dataframe 
df.columns = ['name', 'id', 'nametype', 'recclass', 'mass (g)', 'fall', 'year', 'reclat', 'reclong', 'GeoLocation']

This is the output:

name id nametype recclass mass (g)  fall                    year  reclat  \
0  Aachen  1    Valid       L5       21  Fell  01/01/1880 12:00:00 AM  50.775   

   reclong            GeoLocation  
0  6.08333  (50.775000, 6.083330)

Upvotes: 0

harpan
harpan

Reputation: 8641

You need:

df = pd.DataFrame(data.T)
df.columns = ['name', 'id',  'nametype',    'recclass',    'mass (g)',    'fall',    'year',    'reclat',  'reclong', 'GeoLocation']

Output:

    name    id  nametype    recclass    mass (g)    fall    year        reclat  reclong GeoLocation
0   Aachen   1  Valid       L5          21          Fell      01/01/1880 12:00:00 AM                      50.775                     6.08333       (50.775000, 6.083330)

Upvotes: 0

Edeki Okoh
Edeki Okoh

Reputation: 1844

You can use the reshape tool to do this. In this case you will want to make sure to access the values of DataFrame, and reshape it so that it is 1 row and as many columns as needed. To do this, you will need to use the following code below:

pv_df = pd.DataFrame(df.values.reshape(1,-1))

Upvotes: 1

Felipe Gonzalez
Felipe Gonzalez

Reputation: 353

What you need is not to pivot, but to transpose the dataframe. Here is the documentation.

df = df.transpose()

Upvotes: 3

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