0 1 4

*args and **kwargs

Instead of running the file with the -i flag, y

>>> first() 'Hi, I'm Elias' >>> second() 'Call me Ester'

Creating a DataFrame by passing a NumPy array with a datetime index using date_range() and labeled columns: In [5]: dates = pd.date_range("20130101", periods=6) In [6]: dates Out[6]: DatetimeIndex(['2013-01-01', '2013-01-02', '2013-01-03', '2013-01-04', '2013-01-05', '2013-01-06'], dtype='datetime64[ns]', freq='D') In [7]: df = pd.DataFrame(np.random.randn(6, 4), index=dates, columns=list("ABCD"))

air_quality.head() Out[19]: date.utc location parameter value 2067 2019-05-07 01:00:00+00:00 London Westminster no2 23.0 1003 2019-05-07 01:00:00+00:00 FR04014 no2 25.0 100 2019-05-07 01:00:00+00:00 BETR801 pm25 12.5 1098 2019-05-07 01:00:00+00:00 BETR801 no2 50.5 1109 2019-05-07 01:00:00+00:00 London Westminster pm25 8.0 Copy to clipboard In [20]: air_quality = pd.merge(air_quality, stations_coord, how="left", on="location") In [21]: air_quality.head() Out[21]: date.utc ... coordinates.longitude 0 2019-05-07 01:00:00+00:00 ... -0.13193 1 2019-05-07 01:00:00+00:00 ... 2.39390 2 2019-05-07 01:00:00+00:00 ... 2.39390 3 2019-05-07 01:00:00+00:00 ... 4.43182 4 2019-05-07 01:00:00+00:00 ... 4.43182 [5 rows x 6 columns] Copy to clipboard Using the merge() function, for each of the rows in the air_quality table, the corresponding coordinates are added from the air_quality_stations_coord table. Both tables have the column location in common which is used as a key to combine the information. By choosing the left join, only the locations available in the air_quality (left) table, i.e. FR04014, BETR801 and London Westminster, end up in the resulting table. The merge function supports multiple join options similar to database-style operations.

Multi-indexing is out of scope for this pandas introduction. For the moment, remember that the function reset_index can be used to convert any level of an index to a column, e.g. air_quality.reset_index(level=0)

air_quality_ = pd.concat([air_quality_pm25, air_quality_no2], keys=["PM25", "NO2"])

Sorting the table on the datetime information illustrates also the combination of both tables, with the parameter column defining the origin of the table (either no2 from table air_quality_no2 or pm25 from table air_quality_pm25): In [13]:

When selecting specific rows and/or columns with loc or iloc, new values can be assigned to the selected data. For example, to assign the name anonymous to the first 3 elements of the fourth column: In [26]:

ith this in mind, let's build up a basic web font example from first principles. It's difficult to demonstrate this using an embedded live ex

1em is the font-size of an element (or the element’s parent if you’re using it to set font-size). So, for example, if an element’s font-size is 16px, then setting its width to 4em would make its width 64px (16 * 4 == 64). 1rem is the font-size of the root element (either :root or html). The math works the same with rem as it did with em