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I am working on my assignment of data visualization. Firstly, I have to check dataset I found, and do the data wrangling if it is necessary. The data consists of several particles index for air quality in Madrid, those data were collected by different stations.

I found some values are missing in the table. How can I check those missing values quickly by tools (python or R or Tableau) and replace those values?

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  • In Python, you can use the pandas module to load the Excel file as a DataFrame

  • Post this, it is easy to substitute the NaN/missing values. Let's say your excel is named madrid_air.xlsx

import pandas as pd df = pd.read_excel('madrid_air.xlsx')

  • Post this, you will have what they call a DataFrame which consists of the data in the excel file in the same tabular format with column names and index. In the DataFrame the missing values will be loaded as NaN values. So in order to get the rows which contains NaN values,

df_nan = df[df.isna()]

  • df_nan will have the rows which has NaN values in them.

Now if you want to fill all those NaN values with let's say 0.

df_zerofill = df.fillna(0)

  • df_zerofill will have the whole DataFrame with all the NaNs substituted with 0.

  • In order to specifically fill columns use the column names.

df[['NO','NO_2']] = df[['NO','NO_2']].fillna(0)

To read up more about handling missing data in DataFrames : https://pandas.pydata.org/pandas-docs/stable/user_guide/missing_data.html

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