To convert a 2D array (or nested list) to a DataFrame in Python, you can use the pandas
library. The pandas
library provides the DataFrame()
function, which allows you to create a DataFrame from a 2D array. Here’s an example:
import pandas as pd
array = [['key1', 'value1'], ['key2', 'value2'], ['key3', 'value3']]
df = pd.DataFrame(array, columns=['Key', 'Value'])
print(df)
In the code above, we import the pandas
library as pd
. We have a 2D array called array
, where each inner list represents a row in the DataFrame. We use the pd.DataFrame()
function, passing in the array
and specifying the column names using the columns
parameter.
The resulting DataFrame df
will have two columns, “Key” and “Value”, with the values populated from the 2D array.
The output will be:
Key Value
0 key1 value1
1 key2 value2
2 key3 value3
Each row of the 2D array corresponds to a row in the DataFrame, and the values are placed in the respective columns.
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