CODEWITHSUNDEEP
pythonpandasnan
Govinda Raju
Govinda Raju

Reputation: 411

how assign "NA" value into new column in python and pandas

I am not able to assign NA values to dataframe and while exporting to_csv file,its shows empty. please suggest.

enter image description here

Looking out put of Data_1 is :

enter image description here

for i in range(1, length):
    Nnw_ = np.array(data_1.iloc[0:(data_1.iloc[0:, i]).count(),[i]])
    rep = np.array(data_2.iloc[0:( data_2.iloc[0:, i]).count(),[i + 1]])
    data_1.replace(Nnw, rep, inplace=True)

Upvotes: 0

Views: 6788

Answers (1)

Valdi_Bo
Valdi_Bo

Reputation: 30971

If you read a DataFrame from a CSV file, it may contain missing values represented a.o. as NA. So the source file can contain e.g.:

data_1,data_2
red,Rose
white,NA
yelow,NA
orange,Orange

But read_csv converts such missing values to np.nan, which are printed as NaN and both columns are of object type.

As of Pandas version 1.0 it is possible to convert such columns to string type:

df = df.convert_dtypes()

Now, when you run df.info(), you will get:

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 4 entries, 0 to 3
Data columns (total 2 columns):
 #   Column  Non-Null Count  Dtype 
---  ------  --------------  ----- 
 0   data_1  4 non-null      string
 1   data_2  2 non-null      string
dtypes: string(2)
memory usage: 192.0 bytes

(compare with the result of df.info() just after read_csv, where the type is object).

This DataFrame can be saved to a CSV file, running e.g. df.to_csv('Output.csv', index=False, na_rep='NA') and the result will be:

data_1,data_2
red,Rose
white,NA
yelow,NA
orange,Orange

Note parameters:

  • index=False - to omit the output of the index,
  • na_rep='NA' - to provide a visible representation of NA values (the default representation is an empty string).

Edit

If you want to replace individual cells with NA, run e.g.:

df.iloc[3,1] = np.nan

Don't worry that you used np.nan. Pandas is clever enough to convert it into NA.

If you copy values from data_2 to data_1, there is no problem. Note that after convert_dtypes both columns area of string type, so NA values can be copied also to data_1.

If you don't want the missing values saved as NA, just drop na_rep parameter from to_csv and they will be save as (the default) empty strings.

Upvotes: 1

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