How to Convert Integers to Strings in Pandas DataFrame?
Last Updated :
01 Jul, 2022
In this article, we’ll look at different methods to convert an integer into a string in a Pandas dataframe. In Pandas, there are different functions that we can use to achieve this task :
- map(str)
- astype(str)
- apply(str)
- applymap(str)
Example 1 : In this example, we’ll convert each value of a column of integers to string using the map(str) function.
Python3
import pandas as pd
dict = { 'Integers' : [ 10 , 50 , 100 , 350 , 700 ]}
df = pd.DataFrame.from_dict( dict )
print (df)
print (df.dtypes)
print ( '\n' )
df[ 'Integers' ] = df[ 'Integers' ]. map ( str )
print (df)
print (df.dtypes)
|
Output :
We can see in the above output that before the datatype was int64 and after the conversion to a string, the datatype is an object which represents a string. Example 2 : In this example, we’ll convert each value of a column of integers to string using the astype(str) function.
Python3
import pandas as pd
dict = { 'Integers' : [ 10 , 50 , 100 , 350 , 700 ]}
df = pd.DataFrame.from_dict( dict )
print (df)
print (df.dtypes)
print ( '\n' )
df[ 'Integers' ] = df[ 'Integers' ].astype( str )
print (df)
print (df.dtypes)
|
Output :
We can see in the above output that before the datatype was int64 and after the conversion to a string, the datatype is an object which represents a string. Example 3 : In this example, we’ll convert each value of a column of integers to string using the apply(str) function.
Python3
import pandas as pd
dict = { 'Integers' : [ 10 , 50 , 100 , 350 , 700 ]}
df = pd.DataFrame.from_dict( dict )
print (df)
print (df.dtypes)
print ( '\n' )
df[ 'Integers' ] = df[ 'Integers' ]. apply ( str )
print (df)
print (df.dtypes)
|
Output :
We can see in the above output that before the datatype was int64 and after the conversion to a string, the datatype is an object which represents a string. Example 4 : All the methods we saw above, convert a single column from an integer to a string. But we can also convert the whole dataframe into a string using the applymap(str) method.
Python3
import pandas as pd
dict = { 'Roll No.' : [ 1 , 2 , 3 , 4 , 5 ], 'Marks' :[ 79 , 85 , 91 , 81 , 95 ]}
df = pd.DataFrame.from_dict( dict )
print (df)
print (df.dtypes)
print ( '\n' )
df = df.applymap( str )
print (df)
print (df.dtypes)
|
Output :
We can see in the above output that before the datatype was int64 and after the conversion to a string, the datatype is an object which represents a string.
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