Преобразование чисел с плавающей запятой в целые числа в фрейме данных Pandas

Опубликовано: 27 Марта, 2022

Давайте посмотрим, как преобразовать float в целое число в Pandas DataFrame. Для этого мы будем использовать метод astype (). Это также можно сделать с помощью метода apply ().

Method 1: Using DataFrame.astype() method

First of all we will create a DataFrame:

# importing the library
import pandas as pd
  
# creating a DataFrame
list = [["Anton Yelchin", 36, 75.2, 54280.20], 
        ["Yul Brynner", 38, 74.32, 34280.30], 
        ["Lev Gorn", 31, 70.56, 84280.50],
        ["Alexander Godunov", 34, 80.30, 44280.80], 
        ["Oleg Taktarov", 40, 100.03, 45280.30],
        ["Dmitriy Pevtsov", 33, 72.99, 70280.25], 
        ["Alexander Petrov", 42, 85.84, 25280.75]]
df = pd.DataFrame(list, columns =["Name", "Age", "Weight", "Salary"])
display(df)

Output :

Example 1 : Converting one column from float to int using DataFrame.astype()

# displaying the datatypes
display(df.dtypes)
  
# converting "Weight" from float to int
df["Weight"] = df["Weight"].astype(int)
  
# displaying the datatypes
display(df.dtypes)

Output :

Example 2: Converting more than one column from float to int using DataFrame.astype()

# displaying the datatypes
display(df.dtypes)
  
# converting "Weight" and "Salary" from float to int
df = df.astype({"Weight":"int", "Salary":"int"}) 
  
# displaying the datatypes
display(df.dtypes)

Output :

Method 2: Using DataFrame.apply() method

First of all we will create a DataFrame.

# importing the module
import pandas as pd
  
# creating a DataFrame
list = [[15, 2.5, 100.22], [20, 4.5, 50.21], 
        [25, 5.2, 80.55], [45, 5.8, 48.86], 
        [40, 6.3, 70.99], [41, 6.4, 90.25], 
        [51, 2.3, 111.90]]
df = pd.DataFrame(list, columns = ["Field_1", "Field_2", "Field_3"],
                  index = ["a", "b", "c", "d", "e", "f", "g"])
display(df)

Output :

Example 1: Converting a single column from float to int using DataFrame.apply(np.int64)

# importing the module
import numpy as np
  
# displaying the datatypes
display(df.dtypes)
  
# converting "Field_2" from float to int
df["Field_2"] = df["Field_2"].apply(np.int64)
  
# displaying the datatypes
display(df.dtypes)

Output :

Example 2: Converting multiple columns from float to int using DataFrame.apply(np.int64)

# displaying the datatypes
display(df.dtypes)
  
# converting "Field_2" and "Field_3" from float to int
df["Field_2"] = df["Field_2"].apply(np.int64)
df["Field_3"] = df["Field_3"].apply(np.int64)
  
# displaying the datatypes
display(df.dtypes)

Output :

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Преобразование чисел с плавающей запятой в целые числа в фрейме данных Pandas

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