i can't pull data by column name?

user_14110835 0
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I just started working with the pandas library. Despite my research, I still haven't figured it out. I want to pull the data for the column named q. But it gives an error. How can I do that?

import pandas as pd
data = pd.read_excel('test1.xlsx')
df = pd.DataFrame(data)
print(df.loc[df['q']])

Error:

            Traceback (most recent call last):
            File "c:/Users/sabca/visual studio code projects/webscraping/pandastest.py", line 11, 
            in <module>
                print(df.loc[df['q']])
            File "C:\Users\sabca\AppData\Local\Programs\Python\Python38\lib\site- 
            packages\pandas\core\indexing.py", line 879, in __getitem__        
                return self._getitem_axis(maybe_callable, axis=axis)
            File "C:\Users\sabca\AppData\Local\Programs\Python\Python38\lib\site- 
            packages\pandas\core\indexing.py", line 1099, in _getitem_axis     
                return self._getitem_iterable(key, axis=axis)
            File "C:\Users\sabca\AppData\Local\Programs\Python\Python38\lib\site- 
            packages\pandas\core\indexing.py", line 1037, in _getitem_iterable
                keyarr, indexer = self._get_listlike_indexer(key, axis, raise_missing=False)
            File "C:\Users\sabca\AppData\Local\Programs\Python\Python38\lib\site- 
            packages\pandas\core\indexing.py", line 1254, in _get_listlike_indexer
                self._validate_read_indexer(keyarr, indexer, axis, raise_missing=raise_missing)
            File "C:\Users\sabca\AppData\Local\Programs\Python\Python38\lib\site- 
            packages\pandas\core\indexing.py", line 1298, in _validate_read_indexer
                raise KeyError(f"None of [{key}] are in the [{axis_name}]")
            KeyError: "None of [Index(['qwe1', 'asdf1', 'adfs4', 'wer7', 'tyu1', 'ghfhg5'], 
            dtype='object')] are in the [index]"
data-science pandas dataframe python
4 Answers

Fixing the data/df confusion

Firstly, there's really no need for the line

df = pd.DataFrame(data)

As data is already a Pandas DataFrame as returned by the pd.read_excel function.

Instead I would suggest ommiting this line and going simply with the following (I will be using df to refer to the Pandas DataFrame generated using this function for the remainder of this answer).

df = pd.read_excel('test1.xlsx')

Returning a Pandas Series from column q

Assuming that q is the name of a column in your df then:

df['q']

Will return a Pandas Series representing the column q.

If you wanted to use df.loc this indexing method takes a range of rows to be returned as the first item and an optional range of columns as the second. Assuming you are seeking to return all rows of the column q you could use.

df.loc[:, 'q']

Returning a Numpy array of values from column q

You could use:

df['q'].values

To return a Numpy array containing the values stored within the q column.

user_120459070

You should not need to use indexing and loc(). Try just:

df.loc[:, 'q']

This gets all rows (:) for the specified column (q).

user_87069160

You can just apply .values property. It will return a numpy array of the values in the pandas column. Like df['q'].values. So import Numpy to work with it.

Another is df['q'] to return pandas series of column q.

I would not use df.loc for hard syntax, still you can try df.loc[:, 'q'] and don't index instead slice in df.loc

user_122698570

You can just use:

print(df['q'])
user_134491080
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