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Python 2021-11-09 00:35:09
drop_na in pandas
# importing pandas module import pandas as pd # making data frame from csv file data = pd.read_csv("nba.csv") # making new data frame with dropped NA values new_data = data.dropna(axis = 0, how ='any') Add solution -
Python 2021-11-04 11:19:10
torch timeseries
# Load dependencies from sklearn.preprocessing import MinMaxScaler # Instantiate a scaler """ This has to be done outside the function definition so that we can inverse_transform the prediction set later on. """ scaler = Min... Add solution -
Python 2021-11-04 08:56:11
pandas read_csv drop column
# Read column names from file cols = list(pd.read_csv("sample_data.csv", nrows =1)) print(cols) # Define unused cols unused = ['col1', 'col2'] # Use list comprehension to remove the unwanted column in **usecol** df= pd.read_csv("sample_data... Add solution
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