Pandas 将列值转换为字符串 |
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使用 apply() 方法将 DataFrame 的列值的数据类型转换为字符串
使用 applymap() 方法将所有 DataFrame 列的数据类型转换为 string
使用 astype() 方法将 DataFrame 列值的数据类型转换为 string
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它将 employees_df Dataframe 中 Score 列的数据类型转换为 string 类型。 |
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