Pandas 将列值转换为字符串

Python 2月前 177

本教程介绍了如何将 DataFrame 的列值的数据类型转换为字符串。

import pandas as pd
employees_df = pd.DataFrame({
    'Name': ["Ayush","Bikram","Ceela","Kusal","Shanty"],
    'Score': [31, 38, 33, 39,35],
    'Age':  [33,34,38,45,37],
})
print(employees_df)

输出：

     Name  Score  Age
0   Ayush     31   33
1  Bikram     38   34
2   Ceela     33   38
3   Kusal     39   45
4  Shanty     35   37

我们将使用上面例子中显示的 DataFrame 来解释如何将 DataFrame 的列值的数据类型转换为字符串。

使用 `apply()` 方法将 DataFrame 的列值的数据类型转换为字符串

import pandas as pd
employees_df = pd.DataFrame({
    'Name': ["Ayush","Bikram","Ceela","Kusal","Shanty"],
    'Score': [31, 38, 33, 39,35],
    'Age':  [33,34,38,45,37],
})
print("DataFrame before Conversion:")
print(employees_df,"\n")
print("Datatype of columns before conversion:")
print(employees_df.dtypes,"\n")
employees_df["Age"]=employees_df["Age"].apply(str)
print("DataFrame after conversion:")
print(employees_df,"\n")
print("Datatype of columns after conversion:")
print(employees_df.dtypes)

输出：

DataFrame before Conversion:
     Name  Score  Age
0   Ayush     31   33
1  Bikram     38   34
2   Ceela     33   38
3   Kusal     39   45
4  Shanty     35   37
Datatype of columns before conversion:
Name     object
Score     int64
Age       int64
dtype: object
DataFrame after conversion:
     Name  Score Age
0   Ayush     31  33
1  Bikram     38  34
2   Ceela     33  38
3   Kusal     39  45
4  Shanty     35  37
Datatype of columns after conversion:
Name     object
Score     int64
Age      object
dtype: object

它将 Age 列的数据类型从 int64 改为代表字符串的 object 类型。

使用 `applymap()` 方法将所有 DataFrame 列的数据类型转换为 `string`

如果我们想将 DataFrame 中所有列值的数据类型改为 string 类型，我们可以使用 applymap() 方法。

import pandas as pd
employees_df = pd.DataFrame({
    'Name': ["Ayush","Bikram","Ceela","Kusal","Shanty"],
    'Score': [31, 38, 33, 39,35],
    'Age':  [33,34,38,45,37],
})
print("DataFrame before Conversion:")
print(employees_df,"\n")
print("Datatype of columns before conversion:")
print(employees_df.dtypes,"\n")
employees_df=employees_df.applymap(str)
print("DataFrame after conversion:")
print(employees_df,"\n")
print("Datatype of columns after conversion:")
print(employees_df.dtypes)

输出：

DataFrame before Conversion:
     Name  Score  Age
0   Ayush     31   33
1  Bikram     38   34
2   Ceela     33   38
3   Kusal     39   45
4  Shanty     35   37
zeppy@zeppy-G7-7588:~/test/Week-01/taddaa$ python3 1.py
DataFrame before Conversion:
     Name  Score  Age
0   Ayush     31   33
1  Bikram     38   34
2   Ceela     33   38
3   Kusal     39   45
4  Shanty     35   37
Datatype of columns before conversion:
Name     object
Score     int64
Age       int64
dtype: object
DataFrame after conversion:
     Name Score Age
0   Ayush    31  33
1  Bikram    38  34
2   Ceela    33  38
3   Kusal    39  45
4  Shanty    35  37
Datatype of columns after conversion:
Name     object
Score    object
Age      object
dtype: object

它将所有 DataFrame 列的数据类型转换为 string 类型，在输出中用 object 表示。

使用 `astype()` 方法将 DataFrame 列值的数据类型转换为 `string`

import pandas as pd
employees_df = pd.DataFrame({
    'Name': ["Ayush","Bikram","Ceela","Kusal","Shanty"],
    'Score': [31, 38, 33, 39,35],
    'Age':  [33,34,38,45,37],
})
print("DataFrame before Conversion:")
print(employees_df,"\n")
print("Datatype of columns before conversion:")
print(employees_df.dtypes,"\n")
employees_df["Score"]=employees_df["Score"].astype(str)
print("DataFrame after conversion:")
print(employees_df,"\n")
print("Datatype of columns after conversion:")
print(employees_df.dtypes)

输出：

DataFrame before Conversion:
     Name  Score  Age
0   Ayush     31   33
1  Bikram     38   34
2   Ceela     33   38
3   Kusal     39   45
4  Shanty     35   37
Datatype of columns before conversion:
Name     object
Score     int64
Age       int64
dtype: object
DataFrame after conversion:
     Name Score  Age
0   Ayush    31   33
1  Bikram    38   34
2   Ceela    33   38
3   Kusal    39   45
4  Shanty    35   37
Datatype of columns after conversion:
Name     object
Score    object
Age       int64
dtype: object