Method 5 : Convert string/object type column to int using astype() method with dictionary Method 6 : Convert string/object type column to int using astype() method by specifying data types Method 7 : Convert to int using convert_dtypes() Summary References Different methods to convert...
Convert Column to Int (Integer) You can use pandasDataFrame.astype()function to convert column to int(integer). You can apply this to a specific column or to an entire DataFrame. To cast the data type to a 64-bit signed integer, you can use numpy.int64, numpy.int_, int64, or int a...
0to1Datacolumns(total3columns):# Column Non-Null Count Dtype---0year2non-nullint641month2non-nullobject2day2non-nullint64dtypes:int64(2),object(1)memory usage:176.0+bytes 此外这里再延伸一下,去掉
y object dtype: object After using to_numeric() function x int64 y int64 dtype: object In the above code, the apply() function is used along with the to_numeric() function on the given DataFrame to convert multiple columns into int at once. Further reading: Pandas convert column to flo...
# Convert string to an integer df["Fee"] = df["Fee"].astype(int) print (df.dtypes) # Change specific column type df.Fee = df['Fee'].astype('int') print(df.dtypes) # Output: # Courses object # Fee int32 # Duration object ...
<class'pandas.core.frame.DataFrame'>RangeIndex:4entries,0to3Datacolumns(total8columns):# Column Non-Null Count Dtype---0string_col4non-nullobject1int_col4non-nullint642float_col4non-nullfloat643mix_col4non-nullobject4missing_col3non-nullfloat645money_col4non-nullobject6boolean_col4non-null...
Int Float Object Boolean DatetimeConverting entire pandas dataframe to integersAll these data types can be converted into some other data types using the astype() method. This method is used when we want to convert the data type of one single column or a series, but if we want to convert ...
# import pandas libraryimportpandasaspd# dictionaryData = {'Name':['GeeksForGeeks','Python'],'Unique ID':['900','450']}# create a dataframe objectdf = pd.DataFrame(Data)# convert string to an integerdf['Unique ID'] = df['Unique ID'].astype(int)# show the dataframeprint(df) ...
RangeIndex: 4 entries, 0 to 3 Data columns (total 8 columns): # Column Non-Null Count Dtype --- --- --- --- 0 string_col 4 non-null object 1 int_col 4 non-null int64 2 float_col 4 non-null float64 3 mix_col 4 non-null ...
Convert an Object-Type Column to Float in Pandas An object-type column contains a string or a mix of other types, whereas a float contains decimal values. We will work on the following DataFrame in this article. importpandasaspd df=pd.DataFrame([["10.0",6,7,8],["1.0",9,12,14],["...