Python | Pandas DataFrame.to_records

Pandas DataFrame is a two-dimensional size-mutable, potentially heterogeneous tabular data structure with labeled axes (rows and columns). Arithmetic operations align on both row and column labels. It can be thought of as a dict-like container for Series objects. This is the primary data structure of the Pandas.

Pandas DataFrame.to_records() function convert DataFrame to a NumPy record array. The index will be included as the first field of the record array if requested.

Syntax: DataFrame.to_records(index=True, convert_datetime64=None, column_dtypes=None, index_dtypes=None)

Parameter :
index : bool, default True
convert_datetime64 : Whether to convert the index to datetime.datetime if it is a DatetimeIndex.
column_dtypes : If a string or type, the data type to store all columns
index_dtypes : If a string or type, the data type to store all index levels

Returns : numpy.recarray

Example #1: Use DataFrame.to_records() function to convert the given Dataframe to a numpy record array.

# importing pandas as pd
import pandas as pd

# Creating the DataFrame
df = pd.DataFrame({'Weight':[45, 88, 56, 15, 71],
                   'Name':['Sam', 'Andrea', 'Alex', 'Robin', 'Kia'],
                   'Age':[14, 25, 55, 8, 21]})

# Create the index
index_ = pd.date_range('2010-10-09 08:45', periods = 5, freq ='H')

# Set the index
df.index = index_

# Print the DataFrame
print(df)

Output :

Now we will use DataFrame.to_records() function to convert the given dataframe to a numpy record array representation.

# convert to numpy record array
result = df.to_records()

# Print the result
print(result)

Output :

As we can see in the output, the DataFrame.to_records() function has successfully converted the given dataframe to a numpy record array representation.

Example #2: Use DataFrame.to_records() function to convert the given Dataframe to a numpy record array.

# importing pandas as pd
import pandas as pd

# Creating the DataFrame
df = pd.DataFrame({"A":[12, 4, 5, None, 1],
                   "B":[7, 2, 54, 3, None],
                   "C":[20, 16, 11, 3, 8],
                   "D":[14, 3, None, 2, 6]})

# Create the index
index_ = ['Row_1', 'Row_2', 'Row_3', 'Row_4', 'Row_5']

# Set the index
df.index = index_

# Print the DataFrame
print(df)

Output :

Now we will use DataFrame.to_records() function to convert the given dataframe to a numpy record array representation.

# convert to numpy record array
result = df.to_records()

# Print the result
print(result)

Output :

As we can see in the output, the DataFrame.to_records() function has successfully converted the given dataframe to a numpy record array representation.