DS DataFrame

Create a DataFrame with Pandas

A data frame is a structured format for representing data.

Let’s define a data frame with 3 columns and 5 rows, containing fictional numbers:

import pandas as pd

d = {‘col1’: [1, 2, 3, 4, 7], ‘col2’: [4, 5, 6, 9, 5], ‘col3’: [7, 8, 12, 1, 11]}

df = pd.DataFrame(data=d)

print(df)

Example Explanation

We use pd. before DataFrame() to indicate that we want to call the DataFrame() function from the Pandas library.

Note the capitalization of both the “D” and “F” in DataFrame!

Here is the output:

img_dataframe_output

We can see that “col1”, “col2”, and “col3” are the column names.

The vertical numbers from 0 to 4 represent the row positions.

In Python, row numbering starts at zero.

Now, we can use Python to count the columns and rows.

To find the number of columns, we can use df.shape[1]:

To count the number of columns:

count_column = df.shape[1]
print(count_column)

To find the number of rows, we can use df.shape[0]:

To count the number of rows:

count_row = df.shape[0]
print(count_row)