Programmatically convert pandas dataframe to markdown table

Improving the answer further, for use in IPython Notebook:

def pandas_df_to_markdown_table(df):    from IPython.display import Markdown, display    fmt = ['---' for i in range(len(df.columns))]    df_fmt = pd.DataFrame([fmt], columns=df.columns)    df_formatted = pd.concat([df_fmt, df])    display(Markdown(df_formatted.to_csv(sep="|", index=False)))pandas_df_to_markdown_table(infodf)

Or use tabulate:

pip install tabulate

Examples of use are in the documentation.

I recommend python-tabulate library for generating ascii-tables. The library supports pandas.DataFrame as well.

Here is how to use it:

from pandas import DataFramefrom tabulate import tabulatedf = DataFrame({    "weekday": ["monday", "thursday", "wednesday"],    "temperature": [20, 30, 25],    "precipitation": [100, 200, 150],}).set_index("weekday")print(tabulate(df, tablefmt="pipe", headers="keys"))

Output:

| weekday   |   temperature |   precipitation ||:----------|--------------:|----------------:|| monday    |            20 |             100 || thursday  |            30 |             200 || wednesday |            25 |             150 |

Pandas 1.0 was released 29 january 2020 and supports markdown conversion, so you can now do this directly!

Example taken from the docs:

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 |

Or without the index:

print(df.to_markdown(index=False)) # use 'showindex' for pandas < 1.1

|   A |   B ||----:|----:||   1 |   1 ||   2 |   2 ||   3 |   3 |