stack overflow
bro i got banned from stackoverflowstack over flow
from PIL import Image
user_path = "/Users/" + getpass.getuser())
for folder, sub_folders, files in os.walk(user_path):
for f in files:
if FileName == f:
print("file found", os.path.join(folder,f))stack overflow
MyList:
def __init__(self,my_list= None, levels = None):
if my_list is None:
my_list= []
self.my_list= my_list
if levels is None:
levels = []
self.levels = levels
MyDict:
def __init__(self,my_dict= None, levels = None):
if my_dictis None:
my_dict= {}
for lvl in levels:
my_dict[lvl] = []
self.my_dict = my_dict
if levels is None:
levels = []
self.levels = levels
MyElem:
def __init__(self,my_attribute):
self.my_attribute = my_attributestackoverflow
function myCatch (callback) {
const e = new Error('oh no')
callback<e...>
}
function next (error) {
console.log('got error:', error)
}
myCatch(next)
// Result is: you get `got error: Error: oh no`stack overflow
yeah this is awesome . lol follow me on insta - kiritocode1stackoverflow
import os
import pandas as pd
from sklearn.model_selection import train_test_split
import tensorflow as tf
import numpy as np
from sklearn import metrics
from keras.models import Sequential
from keras.layers.core import Dense, Activation
from keras.callbacks import EarlyStopping
from keras.callbacks import ModelCheckpoint
from keras.preprocessing.text import one_hot
df = pd.read_csv("file.csv")
df.drop('Name', axis=1, inplace=True).
obj_df = df.select_dtypes(include=['object']).copy()
# print(obj_df.head())
obj_df["OUTPUT"] = obj_df["OUTPUT"].astype('category')
obj_df["TYPE_A"] = obj_df["TYPE_A"].astype('category')
obj_df["SIGNAL"] = obj_df["SIGNAL"].astype('category')
obj_df["A-B"] = obj_df["A-B"].astype('category')
# obj_df.dtypes
obj_df["OUTPUT_cat"] = obj_df["OUTPUT"].cat.codes
obj_df["TYPE_A_cat"] = obj_df["TYPE_A"].cat.codes
obj_df["SIGNAL_cat"] = obj_df["SIGNAL"].cat.codes
obj_df["A-B_cat"] = obj_df["A-B"].cat.codes
# print(obj_df.head())
df2 = df[['TRY', 'LOC']]
df3 = obj_df[['OUTPUT_cat', 'TYPE_A_cat', 'SIGNAL_cat', 'A-B_cat']]
df4 = pd.concat([df2, df3], axis=1, sort=False)Copyright © 2021 Codeinu
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