Skip to main content

Unnamed: 0" column impossible to erase

Hello I have a code that filters some rows of a csv and creates a csv without those rows but when I create that csv I get a column called "Unnamed: 0" and it is impossible to delete it.

import pandas as pd

df = pd.read_csv("table.csv")
df.drop(df[df['Stock'].eq('No')].index, inplace=True)
df.to_csv('pedro.csv', index=False )

I have tried everything, I have even set index = False but it still comes out.

And I have also tried using drop

import pandas as pd

df2= pd.read_csv("pedro.csv")
df2.drop("Unnamed: 0", axis=1)

But it still doesn't work because it returns this:

   Unnamed: 0                                  Titulo        Precio Stock Ultima Vez
0           0  RPi CM4 - 8GB RAM, 32GB MMC, With Wifi  (EUR) 120.52   Yes  20-Nov-22
1           1      RPi CM4 - 2GB RAM, No MMC, No Wifi   (EUR) 44.40   Yes  20-Nov-22
2           2    RPi CM4 - 1GB RAM, 32GB MMC, No Wifi   (EUR) 57.08   Yes  20-Nov-22
3           3    RPi CM4 - 1GB RAM, 16GB MMC, No Wifi   (EUR) 50.74   Yes  20-Nov-22
4           4     RPi CM4 - 1GB RAM, 8GB MMC, No Wifi  (PLN) 279.00   Yes  20-Nov-22


source https://stackoverflow.com/questions/74511461/unnamed-0-column-impossible-to-erase

Comments

Popular posts from this blog

ValueError: X has 10 features, but LinearRegression is expecting 1 features as input

So, I am trying to predict the model but its throwing error like it has 10 features but it expacts only 1. So I am confused can anyone help me with it? more importantly its not working for me when my friend runs it. It works perfectly fine dose anyone know the reason about it? cv = KFold(n_splits = 10) all_loss = [] for i in range(9): # 1st for loop over polynomial orders poly_order = i X_train = make_polynomial(x, poly_order) loss_at_order = [] # initiate a set to collect loss for CV for train_index, test_index in cv.split(X_train): print('TRAIN:', train_index, 'TEST:', test_index) X_train_cv, X_test_cv = X_train[train_index], X_test[test_index] t_train_cv, t_test_cv = t[train_index], t[test_index] reg.fit(X_train_cv, t_train_cv) loss_at_order.append(np.mean((t_test_cv - reg.predict(X_test_cv))**2)) # collect loss at fold all_loss.append(np.mean(loss_at_order)) # collect loss at order plt.plot(np.log(al...

Sorting large arrays of big numeric stings

I was solving bigSorting() problem from hackerrank: Consider an array of numeric strings where each string is a positive number with anywhere from to digits. Sort the array's elements in non-decreasing, or ascending order of their integer values and return the sorted array. I know it works as follows: def bigSorting(unsorted): return sorted(unsorted, key=int) But I didnt guess this approach earlier. Initially I tried below: def bigSorting(unsorted): int_unsorted = [int(i) for i in unsorted] int_sorted = sorted(int_unsorted) return [str(i) for i in int_sorted] However, for some of the test cases, it was showing time limit exceeded. Why is it so? PS: I dont know exactly what those test cases were as hacker rank does not reveal all test cases. source https://stackoverflow.com/questions/73007397/sorting-large-arrays-of-big-numeric-stings

How to load Javascript with imported modules?

I am trying to import modules from tensorflowjs, and below is my code. test.html <!DOCTYPE html> <html lang="en"> <head> <meta charset="UTF-8"> <title>Document</title </head> <body> <script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@2.0.0/dist/tf.min.js"></script> <script type="module" src="./test.js"></script> </body> </html> test.js import * as tf from "./node_modules/@tensorflow/tfjs"; import {loadGraphModel} from "./node_modules/@tensorflow/tfjs-converter"; const MODEL_URL = './model.json'; const model = await loadGraphModel(MODEL_URL); const cat = document.getElementById('cat'); model.execute(tf.browser.fromPixels(cat)); Besides, I run the server using python -m http.server in my command prompt(Windows 10), and this is the error prompt in the console log of my browser: Failed to loa...