Performance considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 343 2.5 Indexing and selecting data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . rows x 12 columns] This tutorial uses air quality data about ??2 and Particulate matter less than 2.5 micrometers, made available by openaq and using the py-openaq package. The air_quality_long.csv data section on pivoting DataFrame objects. Pivot table I want the mean concentrations for ??2 and ??2.5 in each of the stations in table form In [14]: air_quality.pivot_table(values="value", index="location"

Performance considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 343 2.5 Indexing and selecting data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 373450 8.0500 NaN S This tutorial uses air quality data about ??2 and Particulate matter less than 2.5 micrometers, made available by openaq and using the py-openaq package. The air_quality_long.csv data Python data analysis toolkit, Release 1.1.0 Pivot table I want the mean concentrations for ??2 and ??2.5 in each of the stations in table form In [14]: air_quality.pivot_table(values="value", index="location"

Performance considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 405 2.5 Indexing and selecting data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . rows x 12 columns] This tutorial uses air quality data about ??2 and Particulate matter less than 2.5 micrometers, made available by openaq and using the py-openaq package. The air_quality_long.csv data section on pivoting DataFrame objects. Pivot table I want the mean concentrations for ??2 and ??2.5 in each of the stations in table form In [14]: air_quality.pivot_table( ....: values="value", index="location"

Performance considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 405 2.5 Indexing and selecting data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 373450 8.0500 NaN S This tutorial uses air quality data about ??2 and Particulate matter less than 2.5 micrometers, made available by openaq and using the py-openaq package. The air_quality_long.csv data section on pivoting DataFrame objects. Pivot table I want the mean concentrations for ??2 and ??2.5 in each of the stations in table form In [14]: air_quality.pivot_table( ....: values="value", index="location"

Performance considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 345 2.5 Indexing and selecting data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . rows x 12 columns] This tutorial uses air quality data about ??2 and Particulate matter less than 2.5 micrometers, made available by openaq and using the py-openaq package. The air_quality_long.csv data section on pivoting DataFrame objects. Pivot table I want the mean concentrations for ??2 and ??2.5 in each of the stations in table form In [14]: air_quality.pivot_table( ....: values="value", index="location"

Performance considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 388 2.5 Indexing and selecting data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . rows x 12 columns] This tutorial uses air quality data about ??2 and Particulate matter less than 2.5 micrometers, made available by openaq and using the py-openaq package. The air_quality_long.csv data section on pivoting DataFrame objects. Pivot table I want the mean concentrations for ??2 and ??2.5 in each of the stations in table form In [14]: air_quality.pivot_table( ....: values="value", index="location"

}} 142 Chapter 2. Getting started pandas: powerful Python data analysis toolkit, Release 1.0.0 2.5 Intro to data structures We’ll start with a quick, non-comprehensive overview of the fundamental data Series(np.random.randn(5)) Out[6]: 0 -1.202857 1 -1.577769 2 0.645254 (continues on next page) 2.5. Intro to data structures 143 pandas: powerful Python data analysis toolkit, Release 1.0.0 (continued section. Like a NumPy array, a pandas Series has a dtype. In [18]: s.dtype Out[18]: dtype('float64') 2.5. Intro to data structures 145 pandas: powerful Python data analysis toolkit, Release 1.0.0 This is

Performance considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 345 2.5 Indexing and selecting data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . rows x 12 columns] This tutorial uses air quality data about ??2 and Particulate matter less than 2.5 micrometers, made available by openaq and using the py-openaq package. The air_quality_long.csv data section on pivoting DataFrame objects. Pivot table I want the mean concentrations for ??2 and ??2.5 in each of the stations in table form In [14]: air_quality.pivot_table( ....: values="value", index="location"

Performance considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 407 2.5 Indexing and selecting data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . rows x 12 columns] This tutorial uses air quality data about ??2 and Particulate matter less than 2.5 micrometers, made available by openaq and using the py-openaq package. The air_quality_long.csv data section on pivoting DataFrame objects. Pivot table I want the mean concentrations for ??2 and ??2.5 in each of the stations in table form In [14]: air_quality.pivot_table( ....: values="value", index="location"

Performance considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 407 2.5 Indexing and selecting data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . rows x 12 columns] This tutorial uses air quality data about ??2 and Particulate matter less than 2.5 micrometers, made available by openaq and using the py-openaq package. The air_quality_long.csv data section on pivoting DataFrame objects. Pivot table I want the mean concentrations for ??2 and ??2.5 in each of the stations in table form In [14]: air_quality.pivot_table( ....: values="value", index="location"