What is `MNaN`??

I am trying to debug some d3 code and in the console debugger I'm getting the following error returned: Error: <...

Python/Pandas: counting the number of missing/NaN in each row?

I've got a dataset with a big number of rows. Some of the values are NaN, like this: In [91]: df Out[91]: 1 3 ...

AttributeError: 'float' object has no attribute 'split'?

I am calling this line: lang_modifiers = [keyw.strip() for keyw in row["language_modifiers"].split("|") if not isin...

Error while creating heatmaps - NA/NaN/Inf in foreign function call (arg 11)?

I'm trying to prepare heatmap for my data but I have no idea why this error appears. My data: > dput(head(tbl_r...

Adding two 2D NumPy arrays ignoring NaNs in them?

What is the right way to add 2 numpy arrays a and b (both 2D) with numpy.nan as missing value? a + b or numpy....

Java isNan how it works??

I was looking at the openjdk-1.7.0_25 source code and I have seen this method: /** * Returns {@code true} if the s...

How to check if any value is NaN in a Pandas DataFrame?

In Python Pandas, what's the best way to check whether a DataFrame has one (or more) NaN values? I know about the f...

How to replace NaN values by Zeroes in a column of a Pandas Dataframe??

I have a Pandas Dataframe as below: itm Date Amount 67 420 2012-09-30 00:00:00 65211 68...

C/C++ NaN constant (literal)??

Is this possible to assign a NaN to a double or float in C/C++? Like in JavaScript you do: a = NaN. So later you can...

How to replace NaN values by Zeroes in a column of a Pandas Dataframe??

I have a Pandas Dataframe as below: itm Date Amount 67 420 2012-09-30 00:00:00 65211 68...

convert nan value to zero?

I have a 2D numpy array. Some of the values in this array are NaN. I want to perform certain operations using this a...

how to test if a variable is pd.NaT??

I'm trying to test if one of my variables is pd.NaT. I know it is NaT, and still it won't pass the test. As an examp...

How to filter in NaN (pandas)??

I have a pandas dataframe (df), and I want to do something like: newdf = df[(df.var1 == 'a') & (df.var2 == NaN)...

How do I get a summary count of missing/NaN data by column in 'pandas'??

In R I can quickly see a count of missing data using the summary command, but the equivalent pandas DataFrame method...