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Below is my dataframe:
Id,ReturnCreated,ReturnTime,TS_startTime
O108808972773560,Return Not Created,nan,2018-08-23 12:30:41
O100497888936380,Return Not Created,nan,2018-08-18 14:57:20
O109648374050370,Return Not Created,nan,2018-08-16 13:50:06
O112787613729150,Return Not Created,nan,2018-08-16 13:15:26
O110938305325240,Return Not Created,nan,2018-08-22 11:03:37
O110829757146060,Return Not Created,nan,2018-08-21 16:10:37
I want to replace the nan with Blanks. Tried the below code, but its not working.
import pandas as pd
import numpy as np
df = pd.concat({k:pd.Series(v) for k, v in ordercreated.items()}).unstack().astype(str).sort_index()
df.columns = 'ReturnCreated ReturnTime TS_startTime'.split()
df1 = df.replace(np.nan,"", regex=True)
df1.to_csv('OrderCreationdetails.csv')
Kindly help me understand where i am going wrong and how can i fix the same.
367
To remove NaN from a list using Python, the easiest way is to use the isnan() function from the Python math module and list comprehension. You can also use the Python filter() function. The Python numpy module also provides an isnan() function that we can use to check if a value is NaN.
You should try DataFrame.fillna() method
https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.fillna.html
In your case:
df1 = df.fillna("")
should work I think
161
I think nans are strings, because .astype(str). So need:
df1 = df.replace('nan',"")
Either you can use df.fillna("") (i think that will perform better) or simple replace that values with blank
df1 = df.replace('NaN',"")
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