如何在大型 pandas dataframe 上显示所有列的名称？

Question

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?

Answer 1

You can globally set printing options. I think this should work:

Method 1:

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

Method 2:

pd.options.display.max_columns = None
pd.options.display.max_rows = None

This will allow you to see all column names & rows when you are doing .head() . None of the column name will be truncated.

---

If you just want to see the column names you can do:

print(df.columns.tolist())

Answer 2

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']

Answer 3

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 .

Answer 4

In the interactive console, it's easy to do:

data_all2.columns.tolist()

Or this within a script:

print(data_all2.columns.tolist())

Answer 5

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.

Answer 6

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.

Answer 7

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.

Answer 8

你可以试试这个

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

Answer 9

The accepted answer caused my column names to wrap around. To show all the column names without wrapping, set both display.max_columns and the display.width :

pandas.set_option('display.max_columns', None)
pandas.set_option('display.width', 1000)

Answer 10

You can do like this

df.info(show_counts=True)

It will show all the columns. Setting show_counts to True shows the count of not_null data.

Answer 11

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

Answer 12

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.

Answer 13

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)

Answer 14

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]

Answer 15

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

Credit: https://stackoverflow.com/a/40435354/5846417

Answer 16

I may be off the mark but I came to this thread with the same type of problem I found this is the simple answer if you want to see everything in a long list and the index.

This is what I use in Spyder:

print(df.info()) 

or this be what is needed in Jupyter:

df.info()

Answer 17

“df.types”将数据框“df”的所有列作为行输出，作为附带奖励，您还将获得数据类型。

Answer 18

Try this one -

df.columns.values

Answer 19

df.head(None)

In this way, you can see all things with a format data frame. You need to write

data_all2.head(None)

Answer 20

My go-to function to print every column on my console is:

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

Answer 21

for i in df2.columns.tolist(): print(i)