Hello Guys, How are you all? Hope You all Are Fine. Today I am trying to read cvs with pandas But I am facing following error **ValueError: cannot convert float NaN to integer** **in python**. So Here I am Explain to you all the possible solutions here.

Without wasting your time, Let’s start This Article to Solve This Error.

Table of Contents

## How ValueError: cannot convert float NaN to integer Error Occurs?

I am trying to read cvs with pandas But I am facing following error.

ValueError: cannot convert float NaN to integer

## How To Solve ValueError: cannot convert float NaN to integer Error ?

**How To Solve ValueError: cannot convert float NaN to integer Error ?**To Solve ValueError: cannot convert float NaN to integer Error You have to convert int into float first. Here is my example. The size of the int if it's 32 or 64 depends on your variable, be aware you may loose some precision if your numbers are to big for the format. Second solution is You can use

`.loc`

to subset the dataframe by only values that are`notnull()`

, and then subset out the`'x'`

column only. Take that same vector, and`apply(int)`

to it.**ValueError: cannot convert float NaN to integer**To Solve ValueError: cannot convert float NaN to integer Error You have to convert int into float first. Here is my example. The size of the int if it's 32 or 64 depends on your variable, be aware you may loose some precision if your numbers are to big for the format. Second solution is You can use

`.loc`

to subset the dataframe by only values that are`notnull()`

, and then subset out the`'x'`

column only. Take that same vector, and`apply(int)`

to it.

## Solution 1: convert int into float first

You have to convert int into float first. Here is my example. The size of the int if it’s 32 or 64 depends on your variable, be aware you may loose some precision if your numbers are to big for the format.

df['column_name'].astype(np.float).astype("Int32")

## Solution 2: `apply(int)`

to it

You can use `.loc`

to subset the dataframe by only values that are `notnull()`

, and then subset out the `'x'`

column only. Take that same vector, and `apply(int)`

to it.

**Here If column x is float:**

df.loc[df['x'].notnull(), 'x'] = df.loc[df['x'].notnull(), 'x'].apply(int)

**Summery**

It’s all About this issue. Hope all solution helped you a lot. Comment below Your thoughts and your queries. Also, Comment below which solution worked for you? Thank You.

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