Like

if hi == hi: print "hi"  elif hi (does not equal) bye:      print "no hi"

Is there something equivalent to == that means "not equal"?

Hi. I possess a pandas dataframe and I am seeking to identify the index of a specific entry within it.

Name Age
0 Mike 23
1 Eric 25
2 Donna 23
3 Will 23  

This is the dataframe. I want to find the index of Donna. How can I do it?

I am developing a program that processes a file by first checking if the initial line is not empty. If it contains content, the program proceeds to read the subsequent four lines. Calculations are then executed based on these lines before moving on to the next line. If this next line is also not empty, the program continues its operation. However, I am encountering the following error:

ValueError: invalid literal for int() with base 10: ''.` 

It is reading the first line but can't convert it to an integer.

What can I do to fix this problem?

I am unable to import this file it showing an error :

import pandas as pd  a = pd.read_csv("xyz.csv")

Below is the code:

library(tidyverse)  df <- tibble(      ~col1, ~col2, ~col3,      1, 2, 3,       1, NA, 3,       NA, 2, 3  )

I can remove all NA abservations with the help of drop_na():

df %>% drop_na()

Or remove all NA in a single column (col1 for example):

df %>% drop_na(col1)

Why I cannot just use a regular != filter pipe ?

df %>% filter(col1 != NA)

Why do we use a special function from tidyr to remove NAs?

def example(p,q): 
a = p.find(" ")  
b = q.find(" ")  
str_p = p[0:a]  
str_q = p[b+1:]  
if str_p == str_q:   
result = True  else: 
result = False 
return result

And I get the folloeing error:

IndentationError: expected an indented block