Добавить несколько столбцов в фрейм данных в Pandas
В Pandas у нас есть свобода добавлять столбцы во фрейм данных, когда это необходимо. Есть несколько способов добавить столбцы во фрейм данных Pandas.
Method 1: Add multiple columns to a data frame using Lists
Python3
# importing pandas libraryimport pandas as pd # creating and initializing a nested liststudents = [["jackma", 34, "Sydeny", "Australia"], ["Ritika", 30, "Delhi", "India"], ["Vansh", 31, "Delhi", "India"], ["Nany", 32, "Tokyo", "Japan"], ["May", 16, "New York", "US"], ["Michael", 17, "las vegas", "US"]] # Create a DataFrame objectdf = pd.DataFrame(students, columns=["Name", "Age", "City", "Country"], index=["a", "b", "c", "d", "e", "f"]) # Creating 2 lists "marks" and "gender"marks = [85.4,94.9,55.2,100.0,40.5,33.5]gender = ["M","F","M","F","F","M"] # adding lists as new column to dataframe dfdf["Uni_Marks"] = marksdf["Gender"] = gender # Displaying the Data framedf |
Выход :
Method 2: Add multiple columns to a data frame using Dataframe.assign() method
Python3
# importing pandas libraryimport pandas as pd # creating and initializing a nested liststudents = [["jackma", 34, "Sydeny", "Australia"], ["Ritika", 30, "Delhi", "India"], ["Vansh", 31, "Delhi", "India"], ["Nany", 32, "Tokyo", "Japan"], ["May", 16, "New York", "US"], ["Michael", 17, "las vegas", "US"]] # Create a DataFrame objectdf = pd.DataFrame(students, columns=["Name", "Age", "City", "Country"], index=["a", "b", "c", "d", "e", "f"]) # creating columns "Admissionnum" and "Percentage"# using dataframe.assign() functiondf = df.assign(Admissionnum=[250, 800, 1200, 300, 400, 700], Percentage=["85%", "90%", "75%", "35%", "60%", "80%"]) # Displaying the Data framedf |
Выход :
Method 3: Add multiple columns to a data frame using Dataframe.insert() method
Python3
# importing pandas libraryimport pandas as pd # creating and initializing a nested liststudents = [["jackma", 34, "Sydeny", "Australia"], ["Ritika", 30, "Delhi", "India"], ["Vansh", 31, "Delhi", "India"], ["Nany", 32, "Tokyo", "Japan"], ["May", 16, "New York", "US"], ["Michael", 17, "las vegas", "US"]] # Create a DataFrame objectdf = pd.DataFrame(students, columns=["Name", "Age", "City", "Country"], index=["a", "b", "c", "d", "e", "f"]) # creating columns "Age" and "ID" at # 2nd and 3rd position using # dataframe.insert() functiondf.insert(2, "Marks", [90, 70, 45, 33, 88, 77], True)df.insert(3, "ID", [101, 201, 401, 303, 202, 111], True) # Displaying the Data framedf |
Выход :
Method 4: Add multiple columns to a data frame using Dictionary and zip()
Python3
# importing pandas libraryimport pandas as pd # creating and initializing a nested liststudents = [["jackma", 34, "Sydeny", "Australia"], ["Ritika", 30, "Delhi", "India"], ["Vansh", 31, "Delhi", "India"], ["Nany", 32, "Tokyo", "Japan"], ["May", 16, "New York", "US"], ["Michael", 17, "las vegas", "US"]] # Create a DataFrame objectdf = pd.DataFrame(students, columns=["Name", "Age", "City", "Country"], index=["a", "b", "c", "d", "e", "f"]) # creating 2 lists "ids" and "marks"ids = [11, 12, 13, 14, 15, 16]marks=[85,41,77,57,20,95,96] # Creating columns "ID" and "Uni_marks" # using Dictionary and zip() df["ID"] = dict(zip(ids, df["Name"]))df["Uni_Marks"] = dict(zip(marks, df["Name"])) # Displaying the Data framedf |
Выход :
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