df1=pd.read_csv('/content/drive/MyDrive/exam/annex1.csv')df2=pd.read_csv('/content/drive/MyDrive/exam/annex2.csv')df3=pd.read_csv('/content/drive/MyDrive/exam/annex3.csv')df4=pd.read_csv('/content/drive/MyDrive/exam/annex4.csv')

file_path = "assessment/" file_name = "coffee_sales.csv" index_column = "Date" coffee_sales_df = pd.read_csv(f"{file_path}{file_name}", index_col=index_column) print(coffee_sales_df.shape) # displays (rows,cols) FileNotFoundError: [Errno 2] No such file or directory: 'assessment/coffee_sales.csv' How to fix the error

Assume that you want to read data to a Dataframe and you have written the following code. And also assume that the data file is in the local directory where you are executing the code. Select the correct line of code that will load the data.import pandas as pydatafile_name = 'my-data.csv'col_name = ['name','age','salary','location','class']dataset = pydata.read_csv(file_name, names = col_name)dataset = pd.read_csv(file_name, names = col_name)dataset = pydata.read_csv(url, names = col_name)pydata.read_csv(file_name, names = col_name)

Write syntax to combine dataframes df1 and df2 based on common column named key

What is the proper way to load a CSV file using pandas?1 pointpandas.from_csv(‘data.csv’)pandas.load_csv(‘data.csv’)pandas.read_csv(‘data.csv’)pandas.import_csv(‘data.csv’)

Test Expected Got import pandas as pddataset_filename = 'penguins.csv'data_col = 'bill_depth_mm'tr, mn = clean_mean_df(name=dataset_filename, col_name=data_col)dataset_path = '/var/lib/seaborn-data/'filename = dataset_path + dataset_filenamedf = pd.read_csv(filename)sbefore =df.shapedf.dropna(inplace = True)safter =df.shapetotal_removed = sbefore[0]-safter[0]mean_val = df[data_col].mean()print(total_removed==tr)print(abs(mn-mean_val)/mn>=0 and abs(mn-mean_val)/mn<.1)TrueTrueFalseTrueimport pandas as pddataset_filename = 'mpg.csv'data_col = 'weight'tr, mn = clean_mean_df(name=dataset_filename, col_name=data_col)dataset_path = '/var/lib/seaborn-data/'filename = dataset_path + dataset_filenamedf = pd.read_csv(filename)sbefore =df.shapedf.dropna(inplace = True)safter =df.shapetotal_removed = sbefore[0]-safter[0]mean_val = df[data_col].mean()print(total_removed==tr)print(abs(mn-mean_val)/mn>=0 and abs(mn-mean_val)/mn<.1)TrueTrueFalseTrueimport pandas as pddataset_filename = 'iris.csv'data_col = 'petal_length'tr, mn = clean_mean_df(name=dataset_filename, col_name=data_col)dataset_path = '/var/lib/seaborn-data/'filename = dataset_path + dataset_filenamedf = pd.read_csv(filename)sbefore =df.shapedf.dropna(inplace = True)safter =df.shapetotal_removed = sbefore[0]-safter[0]mean_val = df[data_col].mean()print(total_removed==tr)print(abs(mn-mean_val)/mn>=0 and abs(mn-mean_val)/mn<.1)TrueTrueTrueTrueYour code must pass all tests to earn any marks. Try again.