विशिष्ट डेटाटाइप वाले कॉलम चुनने के लिए, select_dtypes() . का उपयोग करें विधि और शामिल करें पैरामीटर। सबसे पहले, 2 कॉलम के साथ एक DataFrame बनाएं -
dataFrame = pd.DataFrame( { "Student": ['Jack', 'Robin', 'Ted', 'Marc', 'Scarlett', 'Kat', 'John'],"Roll Number": [ 5, 10, 3, 8, 2, 9, 6] } )
अब, 2 कॉलम उनके संबंधित विशिष्ट डेटाटाइप के साथ चुनें -
column1 = dataFrame.select_dtypes(include=['object']).columns column2 = dataFrame.select_dtypes(include=['int64']).columns
उदाहरण
निम्नलिखित कोड है -
import pandas as pd # Create DataFrame dataFrame = pd.DataFrame( { "Student": ['Jack', 'Robin', 'Ted', 'Marc', 'Scarlett', 'Kat', 'John'],"Roll Number": [ 5, 10, 3, 8, 2, 9, 6] } ) print"DataFrame ...\n",dataFrame print"\nInfo of the entire dataframe:\n" # get the description print(dataFrame.info()) # select columns with specific datatype column1 = dataFrame.select_dtypes(include=['object']).columns column2 = dataFrame.select_dtypes(include=['int64']).columns print"Column 1 with object type = ",column1 print"Column 2 with int64 type = ",column2
आउटपुट
यह निम्नलिखित आउटपुट देगा -
DataFrame ... Roll Number Student 0 5 Jack 1 10 Robin 2 3 Ted 3 8 Marc 4 2 Scarlett 5 9 Kat 6 6 John Info of the entire dataframe: <class 'pandas.core.frame.DataFrame'> RangeIndex: 7 entries, 0 to 6 Data columns (total 2 columns): Roll Number 7 non-null int64 Student 7 non-null object dtypes: int64(1), object(1) memory usage: 184.0+ bytes None Column 1 with object type = Index([u'Student'], dtype='object') Column 2 with int64 type = Index([u'Roll Number'], dtype='object')