将列值转换为 Pandas 中的字符串

在本文中，您将学习如何在 Pandas 中将列值转换为字符串。

Pandas DataFrame 只是一个二维数据结构或二维数组，以行和列的形式表示数据。换句话说，它与用于存储数据的矩形网格相比。它是开源的，功能强大，快速且易于使用。基本上，在处理大数据时，我们需要分析、操作和更新它们，而 pandas 的图书馆在这方面起着主导作用。我们可以在的帮助下检查 Pandas 列的类型df.dtypes。基本上，列值由对象、整数等组成。但我们可以将它们转换为字符串。有几种方法可以执行此操作。比如df.astype()- ,casting等。在本文中，我们将探索它们并了解如何在 Pandas 中将列值转换为字符串。让我们创建一个简单的 Pandas DataFrame 并在下面的部分首先检查它的类型：

import pandas as pd

student_df = pd.DataFrame({'Name' : ['Alex', 'Rohit', 'Cole', 'Deven', 'John'],
                           'Marks' : [72, 83, 68, 90, 88]
                          })

print(student_df)
print(student_df.dtypes)

# Output:
#     Name  Marks
# 0   Alex     72
# 1  Rohit     83
# 2   Cole     68
# 3  Deven     90
# 4   John     88

# Name     object
# Marks     int64
# dtype: object

在这里，您可以看到我们创建了一个简单的 Pandas DataFrame 来表示学生的姓名和分数。这个 DataFrame 列的类型是objectand int64。我们将把它们转换成字符串。

示例一：使用将列值转换为字符串astype

import pandas as pd

student_df = pd.DataFrame({'Name' : ['Alex', 'Rohit', 'Cole', 'Deven', 'John'],
                           'Marks' : [72, 83, 68, 90, 88]
                          })

student_df['Name'] = student_df['Name'].astype('string')
student_df['Marks'] = student_df['Marks'].astype('string')
print(student_df.dtypes)

# Output:
# Name     string
# Marks    string
# dtype: object

由于使用此方法，列值的数据类型已从和更改string为。objectint64

示例二：使用将列值转换为字符串casting

import pandas as pd

student_df = pd.DataFrame({'Name' : ['Alex', 'Rohit', 'Cole', 'Deven', 'John'],
                           'Marks' : [72, 83, 68, 90, 88]
                          })

casted_df = student_df.astype({'Name':'string', 'Marks':'int32'})
print(casted_df.dtypes)
# Output:
# Name     string
# Marks     int32
# dtype: object

列的类型是object和in64。我们使用转换来更改其类型，在输出中，您可以看到数据类型是string现在int32。这些是您可以遵循的将列值转换为 Pandas 中的字符串的方法。

文章原文出处：https: //codesource.io/

#python #pandas #strings #values

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