Calculating Number of Values

DataFrame.count() is the method used to find out how many non-null values exist in a DataFrame. It does not count missing (NaN) entries — only actual data. By default, when you call df.count(), it returns the count of non-null values for each column separately.

For example, if you have a DataFrame with 12 rows and columns like Name, UT, Maths, Science, S.St, Hindi, and Eng, calling df.count() will show you that each column has 12 values (assuming no data is missing). The output looks like this.

This tells you the total number of entries in each column.

Counting values row-wise

To count the number of values in each row instead of each column, you pass the argument axis=1. This is useful when you want to know how many subjects or fields a particular student has filled in.

The syntax is:

df.count(axis=1)

For a DataFrame with 12 rows and 7 columns (all filled), the output will be a Series where every row shows 7 — because each row has 7 non-null values:

0     7
1     7
2     7
3     7
4     7
5     7
6     7
7     7
8     7
9     7
10    7
11    7
dtype: int64

Key point to remember

• df.count() → counts column-wise (axis=0 is the default).
• df.count(axis=1) → counts row-wise.

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