05_add_columns.rst

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.. ipython:: python

    import pandas as pd

Data used for this tutorial:

• .. ipython:: python
  
      air_quality = pd.read_csv("data/air_quality_no2.csv", index_col=0, parse_dates=True)
      air_quality.head()
  
  

How to create new columns derived from existing columns

• I want to express the NO_2 concentration of the station in London in mg/m^3.

  (If we assume temperature of 25 degrees Celsius and pressure of 1013 hPa, the conversion factor is 1.882)

  .. ipython:: python
  
      air_quality["london_mg_per_cubic"] = air_quality["station_london"] * 1.882
      air_quality.head()
  
  

  To create a new column, use the square brackets [] with the new column name at the left side of the assignment.

Note

The calculation of the values is done element-wise. This means all values in the given column are multiplied by the value 1.882 at once. You do not need to use a loop to iterate each of the rows!

• I want to check the ratio of the values in Paris versus Antwerp and save the result in a new column.

  .. ipython:: python
  
      air_quality["ratio_paris_antwerp"] = (
          air_quality["station_paris"] / air_quality["station_antwerp"]
      )
      air_quality.head()
  
  

  The calculation is again element-wise, so the / is applied for the values in each row.

Other mathematical operators (+, -, *, /, …) and logical operators (<, >, ==, …) also work element-wise. The latter was already used in the :ref:`subset data tutorial <10min_tut_03_subset>` to filter rows of a table using a conditional expression.

If you need more advanced logic, you can use arbitrary Python code via :meth:`~DataFrame.apply`.

• I want to rename the data columns to the corresponding station identifiers used by OpenAQ.

  .. ipython:: python
  
      air_quality_renamed = air_quality.rename(
          columns={
              "station_antwerp": "BETR801",
              "station_paris": "FR04014",
              "station_london": "London Westminster",
          }
      )
  
  

  .. ipython:: python
  
      air_quality_renamed.head()
  
  

  The :meth:`~DataFrame.rename` function can be used for both row labels and column labels. Provide a dictionary with the keys the current names and the values the new names to update the corresponding names.

The mapping should not be restricted to fixed names only, but can be a mapping function as well. For example, converting the column names to lowercase letters can be done using a function as well:

.. ipython:: python

    air_quality_renamed = air_quality_renamed.rename(columns=str.lower)
    air_quality_renamed.head()

To user guide

Details about column or row label renaming is provided in the user guide section on :ref:`renaming labels <basics.rename>`.

REMEMBER

• Create a new column by assigning the output to the DataFrame with a new column name in between the [].
• Operations are element-wise, no need to loop over rows.
• Use rename with a dictionary or function to rename row labels or column names.

To user guide

The user guide contains a separate section on :ref:`column addition and deletion <basics.dataframe.sel_add_del>`.