Solution

You could use either of the following methods:

Method-1:

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pd.options.display.max_columns = None

Method-2:

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pd.set_option('display.max_columns', None)

# to reset this
pd.reset_option('display.max_columns')

Method-3:

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# assuming df is your dataframe
pd.set_option('display.max_columns', df.columns.size)

# to reset this
pd.reset_option('display.max_columns')

Method-4:

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# assuming df is your dataframe
pd.set_option('max_columns', df.columns.size)

# to reset this
pd.reset_option('max_columns')

To not wrap the output into multiple lines do this

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pd.set_option('display.expand_frame_repr', False)

References

I will recommend you to explore the following resources for more details and examples.

1. How to show all of columns name on pandas dataframe?

2. How do I expand the output display to see more columns of a pandas DataFrame?

3. How to show all columns / rows of a Pandas Dataframe?

As of pandas v15.0, use the parameter, DataFrame.describe(include = 'all') to get a summary of all the columns when the dataframe has mixed column types. The default behavior is to only provide a summary for the numerical columns.

Example:

In[1]:

df = pd.DataFrame({'b': np.arange(5)})
df.describe(include = 'all')

Out[1]:

        b
count   5   5.000000
unique  4   NaN
top     a   NaN
freq    2   NaN
mean    NaN 2.000000
std     NaN 1.581139
min     NaN 0.000000
25%     NaN 1.000000
50%     NaN 2.000000
75%     NaN 3.000000
max     NaN 4.000000

The numerical columns will have NaNs for summary statistics pertaining to objects (strings) and vice versa.

Summarizing only numerical or object columns

1. To call describe() on just the numerical columns use describe(include = [np.number])

2. To call describe() on just the objects (strings) using describe(include = ['O']).

   In[2]:
   
   df.describe(include = [np.number])
   
   Out[3]:
   
            $b
   count   5.000000
   mean    2.000000
   std     1.581139
   min     0.000000
   25%     1.000000
   50%     2.000000
   75%     3.000000
   max     4.000000
   
   In[3]:
   
   df.describe(include = ['O'])
   
   Out[3]:
   
       $a
   count   5
   unique  4
   top     a
   freq    2