Learn how to access rows and columns in Pandas DataFrame, and there are several ways to do it. You can the many way Pandas can index a DataFrame and how to use “loc” and “iloc” to access rows. As a bonus we’ll convert time stamps between time zones.
- [Instructor] Now that we have our data frame…in the right format, let's access some data.…Data can be accessed either by rows or columns.…To get a column, you can use square brackets.…DF, square brackets, and let.…You can also write df.let.…But I don't recommend using dot notation.…In some cases the column names have spaces in them…and then you can't use dot notation anyway.…So get in the habit of using square brackets,…which always work.…
We can pick more than one column.…DF lat and LNG.…If you want a specific value,…you can first select the column…and then the the row.…DF lat at location zero.…Remember that Python is zero based,…so the first line is zero, not one.…If you want an entire row, you can use the dot loc accessor.…Df.loc(0) loc can work with slices as well…df.loc from two to seven.…
Note that unlike usual slices in Python…which are half open, in Pandas…loc slices return both the start and ending digits.…We can also use slices with column selection,…so we'll do DF lat and longitude and then from two to seven.…
- Working with Jupyter notebooks
- Using code cells
- Extensions to the Python language
- Markdown cells
- Editing notebooks
- NumPy basics
- Broadcasting, array operations, and ufuncs
- Folium and Geo
- Machine learning with scikit-learn
- Plotting with matplotlib and bokeh
- Branching into Numba, Cython, deep learning, and NLP
Skill Level Intermediate
1. Scientific Python Overview
2. The Jupyter Notebook
3. NumPy Basics
Manage environments5m 11s
6. Folium and Geo
7. NY Taxi Data
10. Other Packages
11. Development Process
Next steps1m 33s
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