WebMay 9, 2024 · I've tried using .values which throws this error: 'numpy.ndarray' object has no attribute 'values' df4= pd.DataFrame ( {'Actual': y_test.values.flatten (), 'Predicted': y_pred.values.flatten ()}) Y_test definition X_train, X_test, y_train, y_test = train_test_split (X, y, test_size=0.2, random_state=0) WebI've created a Minimal, Complete, and Verifiable example below: import numpy as np import pandas as pd import os import math # get the path to the current working directory cwd = os.getcwd () # then add the name of the Excel file, including its extension to get its relative path # Note: make sure the Excel file is stored inside the cwd file ...
How to resolve AttributeError:
WebJun 21, 2024 · Modified 3 years, 9 months ago Viewed 8k times 1 In python dataframe while getting category codes after assigning a column to variable ( y=df.column) is giving attribute error. . While same is working fine if we directoly pass df.column to Categorical function. python pandas Share Improve this question Follow edited Jun 21, 2024 at … WebSep 7, 2024 · df1.write.mode ("overwrite").saveAsTable ("temp.eehara_trial_table_9_5_19") I don't know what your use case is but assuming you want to work with pandas and you don't know how to connect to the underlying database it is the easiest way to just convert your pandas dataframe to a pyspark dataframe and save it as a table: spark_df = spark ... impact kickboxing isle of man
python - Dataframe object has no attribute - Stack Overflow
WebApr 13, 2024 · Axes from plt.subplots is a "numpy.ndarray" object and has no attribute "plot" (4 answers) closed 2 years ago. questions: fill in the code below to visualize all 100 … WebSep 22, 2015 · head (1) returns an Array, so taking head on that Array causes the java.util.NoSuchElementException when the DataFrame is empty. def head (n: Int): Array [T] = withAction ("head", limit (n).queryExecution) (collectFromPlan) So instead of calling head (), use head (1) directly to get the array and then you can use isEmpty. WebOct 9, 2013 · To pickup from the comment: "I was doing this:" df = [df.hc== 2] What you create there is a "mask": an array with booleans that says which part of the index fulfilled your condition. To filter your dataframe on your condition you want to do this: df = df [df.hc == 2] A bit more explicit is this: mask = df.hc == 2 df = df [mask] impact kickboxing schedule