Let's say we have a pandas dataframe:
name age sal
0 Alex 20 100
1 Jane 15 200
2 John 25 300
3 Lsd 23 392
4 Mari 21 380
Let's say, a few rows are now deleted and we don't know the indexes that have been deleted. For example, we delete row index 1 using df.drop([1]). And now the data frame comes down to this:
fname age sal
0 Alex 20 100
2 John 25 300
3 Lsd 23 392
4 Mari 21 380
I would like to get the value from row index 3 and column "age". It should return 23. How do I do that?
df.iloc[3, df.columns.get_loc('age')] does not work because it will return 21. I guess iloc takes the consecutive row index?
Use .loc to get rows by label and .iloc to get rows by position:
>>> df.loc[3, 'age']
23
>>> df.iloc[2, df.columns.get_loc('age')]
23
More about Indexing and selecting data
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