Move column by name to front of table in pandas

Question

Here is my df:

                             Net   Upper   Lower  Mid  Zsore
Answer option                                                
More than once a da         


        

Answer 1

Maybe I'm missing something, but a lot of these answers seem overly complicated. You should be able to just set the columns within a single list:

Column to the front:

df = df[ ['Mid'] + [ col for col in df.columns if col != 'Mid' ] ]

Or if instead, you want to move it to the back:

df = df[ [ col for col in df.columns if col != 'Mid' ] + ['Mid'] ]

Or if you wanted to move more than one column:

cols_to_move = ['Mid', 'Zsore']
df           = df[ cols_to_move + [ col for col in df.columns if col not in cols_to_move ] ]

Answer 2

You can use the df.reindex() function in pandas. df is

                      Net  Upper   Lower  Mid  Zsore
Answer option                                      
More than once a day  0%  0.22%  -0.12%    2     65
Once a day            0%  0.32%  -0.19%    3     45
Several times a week  2%  2.45%   1.10%    4     78
Once a week           1%  1.63%  -0.40%    6     65

define an list of column names

cols = df.columns.tolist()
cols
Out[13]: ['Net', 'Upper', 'Lower', 'Mid', 'Zsore']

move the column name to wherever you want

cols.insert(0, cols.pop(cols.index('Mid')))
cols
Out[16]: ['Mid', 'Net', 'Upper', 'Lower', 'Zsore']

then use df.reindex() function to reorder

df = df.reindex(columns= cols)

out put is: df

                      Mid  Upper   Lower Net  Zsore
Answer option                                      
More than once a day    2  0.22%  -0.12%  0%     65
Once a day              3  0.32%  -0.19%  0%     45
Several times a week    4  2.45%   1.10%  2%     78
Once a week             6  1.63%  -0.40%  1%     65

Answer 3

Here is a generic set of code that I frequently use to rearrange the position of columns. You may find it useful.

cols = df.columns.tolist()
n = int(cols.index('Mid'))
cols = [cols[n]] + cols[:n] + cols[n+1:]
df = df[cols]

Answer 4

The most simplist thing you can try is:

df=df[[ 'Mid',   'Upper',   'Lower', 'Net'  , 'Zsore']]

Answer 5

I didn't like how I had to explicitly specify all the other column in the other solutions so this worked best for me. Though it might be slow for large dataframes...?

df = df.set_index('Mid').reset_index()

Answer 6

To reorder the rows of a DataFrame just use a list as follows.

df = df[['Mid', 'Net', 'Upper', 'Lower', 'Zsore']]

This makes it very obvious what was done when reading the code later. Also use:

df.columns
Out[1]: Index(['Net', 'Upper', 'Lower', 'Mid', 'Zsore'], dtype='object')

Then cut and paste to reorder.

---

For a DataFrame with many columns, store the list of columns in a variable and pop the desired column to the front of the list. Here is an example:

cols = [str(col_name) for col_name in range(1001)]
data = np.random.rand(10,1001)
df = pd.DataFrame(data=data, columns=cols)

mv_col = cols.pop(cols.index('77'))
df = df[[mv_col] + cols]

Now df.columns has.

Index(['77', '0', '1', '2', '3', '4', '5', '6', '7', '8',
       ...
       '991', '992', '993', '994', '995', '996', '997', '998', '999', '1000'],
      dtype='object', length=1001)