Pretty Printing a pandas dataframe

Question

How can I print a pandas dataframe as a nice text-based table, like the following?

+------------+---------+-------------+
| column_one | col_two |   column_3  |
+------------+---------+-------------+
|          0 |  0.0001 | ABCD        |
|          1 |  1e-005 | ABCD        |
|          2 |  1e-006 | long string |
|          3 |  1e-007 | ABCD        |
+------------+---------+-------------+

Answer 1

I've just found a great tool for that need, it is called tabulate.

It prints tabular data and works with DataFrame.

from tabulate import tabulate
import pandas as pd

df = pd.DataFrame({'col_two' : [0.0001, 1e-005 , 1e-006, 1e-007],
                   'column_3' : ['ABCD', 'ABCD', 'long string', 'ABCD']})

print(tabulate(df, headers='keys', tablefmt='psql'))

+----+-----------+-------------+
|    |   col_two | column_3    |
|----+-----------+-------------|
|  0 |    0.0001 | ABCD        |
|  1 |    1e-05  | ABCD        |
|  2 |    1e-06  | long string |
|  3 |    1e-07  | ABCD        |
+----+-----------+-------------+

Note:

To suppress row indices for all types of data, pass showindex="never" or showindex=False.

Answer 2

pandas >= 1.0

If you want an inbuilt function to dump your data into some github markdown, you now have one. Take a look at to_markdown:

df = pd.DataFrame({"A": [1, 2, 3], "B": [1, 2, 3]}, index=['a', 'a', 'b'])  
print(df.to_markdown()) 
                                               
|    |   A |   B |
|:---|----:|----:|
| a  |   1 |   1 |
| a  |   2 |   2 |
| b  |   3 |   3 |

Here's what that looks like on github:

Note that to_markdown calls tabulate under the hood, so you will still need to have the tabulate package installed. But this means that to_markdown can support 20+ different table formats via keyword arguments that it passes through to tabulate. As an example, you can get the same output as Romain's answer using df.to_markdown(headers='keys', tablefmt='psql')

Answer 3

If you are in Jupyter notebook, you could run the following code to interactively display the dataframe in a well formatted table.

This answer builds on the to_html('temp.html') answer above, but instead of creating a file displays the well formatted table directly in the notebook:

from IPython.display import display, HTML

display(HTML(df.to_html()))

Credit for this code due to example at: Show DataFrame as table in iPython Notebook

Answer 4

A simple approach is to output as html, which pandas does out of the box:

df.to_html('temp.html')

Answer 5

You can use prettytable to render the table as text. The trick is to convert the data_frame to an in-memory csv file and have prettytable read it. Here's the code:

from StringIO import StringIO
import prettytable    

output = StringIO()
data_frame.to_csv(output)
output.seek(0)
pt = prettytable.from_csv(output)
print pt

Answer 6

Following up on Mark's answer, if you're not using Jupyter for some reason, e.g. you want to do some quick testing on the console, you can use the DataFrame.to_string method, which works from -- at least -- Pandas 0.12 (2014) onwards.

import pandas as pd

matrix = [(1, 23, 45), (789, 1, 23), (45, 678, 90)]
df = pd.DataFrame(matrix, columns=list('abc'))
print(df.to_string())

#  outputs:
#       a    b   c
#  0    1   23  45
#  1  789    1  23
#  2   45  678  90

Answer 7

I used Ofer's answer for a while and found it great in most cases. Unfortunately, due to inconsistencies between pandas's to_csv and prettytable's from_csv, I had to use prettytable in a different way.

One failure case is a dataframe containing commas:

pd.DataFrame({'A': [1, 2], 'B': ['a,', 'b']})

Prettytable raises an error of the form:

Error: Could not determine delimiter

The following function handles this case:

def format_for_print(df):    
    table = PrettyTable([''] + list(df.columns))
    for row in df.itertuples():
        table.add_row(row)
    return str(table)

If you don't care about the index, use:

def format_for_print2(df):    
    table = PrettyTable(list(df.columns))
    for row in df.itertuples():
        table.add_row(row[1:])
    return str(table)

Answer 8

Maybe you're looking for something like this:

def tableize(df):
    if not isinstance(df, pd.DataFrame):
        return
    df_columns = df.columns.tolist() 
    max_len_in_lst = lambda lst: len(sorted(lst, reverse=True, key=len)[0])
    align_center = lambda st, sz: "{0}{1}{0}".format(" "*(1+(sz-len(st))//2), st)[:sz] if len(st) < sz else st
    align_right = lambda st, sz: "{0}{1} ".format(" "*(sz-len(st)-1), st) if len(st) < sz else st
    max_col_len = max_len_in_lst(df_columns)
    max_val_len_for_col = dict([(col, max_len_in_lst(df.iloc[:,idx].astype('str'))) for idx, col in enumerate(df_columns)])
    col_sizes = dict([(col, 2 + max(max_val_len_for_col.get(col, 0), max_col_len)) for col in df_columns])
    build_hline = lambda row: '+'.join(['-' * col_sizes[col] for col in row]).join(['+', '+'])
    build_data = lambda row, align: "|".join([align(str(val), col_sizes[df_columns[idx]]) for idx, val in enumerate(row)]).join(['|', '|'])
    hline = build_hline(df_columns)
    out = [hline, build_data(df_columns, align_center), hline]
    for _, row in df.iterrows():
        out.append(build_data(row.tolist(), align_right))
    out.append(hline)
    return "\n".join(out)


df = pd.DataFrame([[1, 2, 3], [11111, 22, 333]], columns=['a', 'b', 'c'])
print tableize(df)

Output:
+-------+----+-----+
|    a  |  b |   c |
+-------+----+-----+
|     1 |  2 |   3 |
| 11111 | 22 | 333 |
+-------+----+-----+

Answer 9

I use the rich library for that, it has nicer looking tables than the tabulate based .to_markdown().

import pandas as pd
from rich.console import Console
from rich.table import Table
df = pd.DataFrame({'col_two' : [0.0001, 1e-005 , 1e-006, 1e-007],
                   'column_3' : ['ABCD', 'ABCD', 'long string', 'ABCD']})
console = Console()
table = Table('Title')
table.add_row(df.to_string(float_format=lambda _: '{:.4f}'.format(_)))
console.print(table)

Gives you this table:

See the documentation for more customization options:

https://rich.readthedocs.io/en/stable/tables.html

Answer 10

Update: an even better solution is to simply put the variable name of the dataframe on the last line of the cell. It will automatically print in a pretty format.

import pandas as pd
import numpy as np

df = pd.DataFrame({'Data1': np.linspace(0,10,11), 'Data2': np.linspace(10,0,11)})
df