I have a dataframe that consist of hundreds of columns, and I need to see all column names.
What I did:
In[37]:
data_all2.columns
The output is:
Out[37]:
Index(['customer_id', 'incoming', 'outgoing', 'awan', 'bank', 'family', 'food',
'government', 'internet', 'isipulsa',
...
'overdue_3months_feature78', 'overdue_3months_feature79',
'overdue_3months_feature80', 'overdue_3months_feature81',
'overdue_3months_feature82', 'overdue_3months_feature83',
'overdue_3months_feature84', 'overdue_3months_feature85',
'overdue_3months_feature86', 'loan_overdue_3months_total_y'],
dtype='object', length=102)
How do I show all columns, instead of a truncated list?
This will do the trick. Note the use of display()
instead of print.
with pd.option_context('display.max_rows', 5, 'display.max_columns', None):
display(my_df)
EDIT:
The use of display
is required because pd.option_context
settings only apply to display
and not to print
.
Not a conventional answer, but I guess you could transpose the dataframe to look at the rows instead of the columns. I use this because I find looking at rows more 'intuitional' than looking at columns:
data_all2.T
This should let you view all the rows. This action is not permanent, it just lets you view the transposed version of the dataframe.
If the rows are still truncated, just use print(data_all2.T)
to view everything.
In the interactive console, it's easy to do:
data_all2.columns.tolist()
Or this within a script:
print(data_all2.columns.tolist())
If you just want to see all the columns you can do something of this sort as a quick fix
cols = data_all2.columns
now cols will behave as a iterative variable that can be indexed. for example
cols[11:20]
What worked for me was the following:
pd.options.display.max_seq_items = None
You can also set it to an integer larger than your number of columns.
you can try this
pd.pandas.set_option('display.max_columns', None)
I know it is a repetition but I always end up copy pasting and modifying YOLO's answer:
pd.set_option('display.max_columns', 500)
pd.set_option('display.max_rows', 500)
To obtain all the column names of a DataFrame, df_data
in this example, you just need to use the command df_data.columns.values
.
This will show you a list with all the Column names of your Dataframe
Code:
df_data=pd.read_csv('../input/data.csv')
print(df_data.columns.values)
Output:
['PassengerId' 'Survived' 'Pclass' 'Name' 'Sex' 'Age' 'SibSp' 'Parch' 'Ticket' 'Fare' 'Cabin' 'Embarked']
To get all column name you can iterate over the data_all2.columns
.
columns = data_all2.columns
for col in columns:
print col
You will get all column names. Or you can store all column names to another list variable and then print list.
The easiest way I've found is just
list(df.columns)
Personally I wouldn't want to change the globals, it's not that often I want to see all the columns names.
I had lots of duplicate column names, and once I ran
df = df.loc[:,~df.columns.duplicated()]
I was able to see the full list of columns
A quick and dirty solution would be to convert it to a string
print('\t'.join(data_all2.columns))
would cause all of them to be printed out separated by tabs Of course, do note that with 102 names, all of them rather long, this will be a bit hard to read through
Source: Stackoverflow.com