Why data cleaning plays a vital role in the analysis?

+1 vote
Nov 19 in Data Analytics by Roopadevi
• 140 points
39 views

1 answer to this question.

+1 vote

Data cleaning is the fourth step in the analysis process and it is one of the most underrated steps. Data is not always ready after its processed. Every data has a lot of redundancies, incorrect and irrelevant data as mentioned earlier. This type of data is called dirty data. and Most of the real-world data sets extracted are dirty.  It’s impossible to make any sort of analysis through it. Most statistical theories focus on data modeling, visualization and analysis assuming the data they’re using is always in the perfect format. That’s seldom the case. In practice, the time spent on preparing the data for analysis is the highest and considered one of the most tiring tasks.

https://www.edureka.co/community/30399/why-is-data-cleaning-needed?

answered Nov 22 by Keshav

Related Questions In Data Analytics

0 votes
2 answers

How does data cleaning play a vital role in data analysis

Data is the core you do your ...READ MORE

answered Jul 23, 2018 in Data Analytics by Anmol
• 3,620 points
299 views
0 votes
1 answer

Finding the nth highest value in a vector or a data-frame column

sort(x,T)[n] Here, 'x' is the data-frame/vector and 'n' ...READ MORE

answered May 31, 2018 in Data Analytics by Bharani
• 4,560 points
480 views
0 votes
1 answer

What are the important skills to have in Python with regard to data analysis?

The following are some of the important ...READ MORE

answered Aug 20, 2018 in Data Analytics by Anmol
• 3,620 points
119 views
0 votes
1 answer

Replace comma with a period in data cleaning using R

You can use the scan function in ...READ MORE

answered Nov 13, 2018 in Data Analytics by Maverick
• 10,040 points
74 views
0 votes
1 answer

Cleaning a Data Frame Using Regexp in R

The simplest way: library(dplyr) library(stringi) df %>% mutate(NUMERO_APPEL.fix = ...READ MORE

answered Nov 13, 2018 in Data Analytics by Maverick
• 10,040 points
31 views
0 votes
2 answers

What are the steps in data analysis process?

Well explained @Maverick, In simple words the ...READ MORE

answered Aug 22 in Data Analytics by anonymous
• 32,260 points
146 views
0 votes
2 answers
+1 vote
2 answers

Custom Function to replace missing values in a vector with the mean of values

Try this. lapply(a,function(x){ifelse(is.na(x),mean(a,na.rm = TRUE) ...READ MORE

answered Aug 14 in Data Analytics by anonymous
105 views
0 votes
2 answers

How to count the number of elements with the values in a vector?

Use dplyr function group_by(). > n = as.data.frame(num) > ...READ MORE

answered Aug 21 in Data Analytics by anonymous
• 32,260 points
134 views