Pandas

Read, manipulate, analyze, and plot data with ease — all within Python! 

Note: This course currently has more than 10 hours of video. When complete, by late July, it will have about 12 hours of video, and the price will increase. Buy now, and you'll automatically have access as new content is added. Look at the syllabus to see what topics are planned.

What's included?

Video Icon 136 videos File Icon 24 files

Contents

published-syllabus.txt
6.5 KB
Section 1: Introduction
Pandas, part 1 -- introduction.ipynb
1.21 KB
1 Introduction.mov
3 mins
2 what-is-pandas.mov
5 mins
3 Installing Pandas.mp4
6 mins
4 Loading Pandas into Jupyter.mp4
6 mins
Section 2: Series
Pandas, part 2 -- series.ipynb
77.2 KB
5 Creating a series.mp4
5 mins
6 Creating a series with NumPy.mp4
4 mins
7 Setting and retrieving with indexes.mp4
5 mins
8 Retrieving with loc and iloc.mp4
5 mins
9 Setting the index.mp4
6 mins
10 Non-unique indexes.mp4
4 mins
10a Fancy indexing.mp4
3 mins
11 Basic methods.mp4
2 mins
12 Operations by index.mp4
3 mins
13 Broadcasting operators.mp4
2 mins
14 Boolean indexing.mp4
3 mins
15 Exercises 1.mp4
2 mins
exercise-1.txt
477 Bytes
16 Exercise solutions 1.mp4
6 mins
Section 3: dtypes and NaN
Pandas, part 3 -- dtypes and NaN.ipynb
67.4 KB
17 dtypes.mp4
8 mins
18 assigning to dtypes.mp4
6 mins
19 Using astype.mp4
6 mins
20 NaN.mp4
3 mins
20a Skipping NaN.mp4
5 mins
21 dropna and fillna.mp4
7 mins
22 fill_value.mp4
6 mins
23 Exercises 2.mp4
2 mins
exercise-2.txt
487 Bytes
24 Exercise solutions 2.mp4
5 mins
Section 4: Advanced series functionality
Pandas, part 4 -- advanced series.ipynb
47.6 KB
25 size and count.mp4
3 mins
26 median and quantiles.mp4
4 mins
27 describe.mp4
4 mins
28 describe with non-numeric data.mp4
2 mins
29 head and tail.mp4
3 mins
30 value_counts.mp4
5 mins
31 duplicated.mp4
3 mins
32 replace.mp4
5 mins
33 Sorting.mp4
5 mins
34 apply.mp4
5 mins
35 Exercises 3.mp4
2 mins
exercise-3.txt
359 Bytes
36 Exercise solutions 3.mp4
6 mins
Section 5: Strings
Pandas, part 5 -- Strings.ipynb
41.7 KB
37 Strings in Pandas vs NumPy.mp4
5 mins
38 String methods and the "str" object.mp4
5 mins
39 Finding numbers.mp4
4 mins
40 startswith and endswith.mp4
3 mins
41 [] and strings.mp4
4 mins
42 str.contains.mp4
4 mins
43 find and index.mp4
6 mins
44 Modifying data.mp4
6 mins
45 Splitting and reusing str.mp4
3 mins
46 Exercises 4.mp4
1 min
exercise-4.txt
220 Bytes
47 Exercise 4 solutions.mp4
5 mins
Section 6: Plotting series
Pandas, part 6 -- plotting.ipynb
760 KB
48 Simple plots with matplotlib.mp4
14 mins
49 More sophisticated plotting with Matplotlib.mp4
11 mins
50 Line plots via pandas.mp4
8 mins
51 Bar plots with pandas.mp4
5 mins
52 Histograms.mp4
5 mins
53 Pie plots.mp4
8 mins
54 Box plots.mp4
6 mins
55 Exercises 5.mp4
2 mins
exercise-5.txt
501 Bytes
56 Exercise 5 solutions.mp4
6 mins
Section 7: Data frames
Pandas, part 7 -- data frames.ipynb
226 KB
57 Data frame introduction.mp4
6 mins
58 Index and columns -- simple retrievals.mp4
6 mins
58a Dot syntax for column retrieval.mp4
2 mins
59 Setting the index and columns.mp4
7 mins
60 Retrieving an individual value.mp4
5 mins
61 Creating data frames from NumPy arrays.mp4
6 mins
62 Creating data frames from a list of dicts.mp4
5 mins
63 Creating data frames from a dict of lists, arrays, or series.mp4
8 mins
64 Methods on columns.mp4
3 mins
65 Methods on an entire data frame.mp4
4 mins
66 Retrieving multiple columns.mp4
6 mins
67 Retrieving multiple rows.mp4
4 mins
68 Updating values in a data frame.mp4
5 mins
68a Using "describe" on data frames.mp4
4 mins
69 Exercises 6.mp4
2 mins
exercise-6.txt
877 Bytes
70 Exercise solutions 6.mp4
10 mins
Section 8: Boolean indexes and data frames
71 Boolean indexes on a column.mp4
4 mins
Pandas, part 8 -- boolean indexes and data frames.ipynb
283 KB
72 Applying boolean indexes to other columns.mp4
8 mins
73 Complex queries across columns.mp4
6 mins
74 Applying a boolean index to an entire data frame.mp4
5 mins
75 Assigning to data frames -- recap.mp4
4 mins
76 Assigning to multiple rows and columns with loc.mp4
4 mins
77 Assigning to a column based on a boolean index.mp4
8 mins
78 Chained assignment -- what it is, and how to avoid it.mp4
4 mins
79 Data frame assignment example.mp4
4 mins
80 Assigning a scalar value to a data frame, based on a condition.mp4
5 mins
81 Assigning a vector value to a data frame, based on a condition.mp4
5 mins
82 Using df.replace to replace values across a data frame.mp4
6 mins
82a Using isna, dropna, and fillna with data frames.mp4
8 mins
82a Using isna, dropna, and fillna with data frames.mp4
8 mins
83 Using mask and where .mp4
4 mins
84 Using clip.mp4
6 mins
68e Dropping one or more rows.mp4
2 mins
68f Dropping one or more columns.mp4
3 mins
85 Exercises 7.mp4
3 mins
68d Updating values in rows and adding rows.mp4
3 mins
exercise-7.txt
1.13 KB
68c Adding columns.mp4
4 mins
86 Exercise solutions 7.mp4
14 mins
68b Updating a column.mp4
6 mins
85 Exercises 7.mp4
3 mins
68a Using "describe" on data frames.mp4
4 mins
86 Exercise solutions 7.mp4
14 mins
Section 9: Pandas and I/O — reading and writing files
Pandas, part 9 -- input and output.ipynb
271 KB
87 Pandas and IO -- and saving to the clipboard.mp4
6 mins
88 Saving to CSV.mp4
6 mins
89 Changing the CSV separator.mp4
6 mins
90 NaN representation.mp4
3 mins
91 Choosing output columns.mp4
3 mins
92 Writing row and column names.mp4
6 mins
93 Saving with compression.mp4
6 mins
94 Reading CSV files.mp4
6 mins
95 Choosing and ignoring header rows.mp4
5 mins
96 Naming columns.mp4
5 mins
97 Choosing columns.mp4
5 mins
98 Choosing + naming.mp4
6 mins
99 Reading NaN values.mp4
4 mins
100 dtype hints when reading CSV.mp4
6 mins
101 Reading from the network.mp4
5 mins
102 Exercises 8.mp4
1 min
exercise-8.txt
524 Bytes
103 Exercise 8 solutions.mp4
6 mins
104 Excel files.mp4
6 mins
105 JSON files.mp4
6 mins
106 SQL databases.mp4
13 mins
Section 10: Data analysis with Pandas
Pandas, part 10 -- analysis of real-world data.ipynb
32.8 KB
flight-delays.zip
186 MB
taxi.csv
1.49 MB
107 Analysis of taxi data.mp4
6 mins
108 Taxi data part 2.mp4
3 mins
109 Taxi data part 3.mp4
5 mins
110 Taxi data part 4.mp4
5 mins
111 Taxi data part 5.mp4
6 mins
112 Taxi data part 6.mp4
6 mins
113 Exercises 9.mp4
3 mins
114 Exercise 9 solutions.mp4
8 mins
Section 11: Memory management and categories
airlines.dat
380 KB
exercise-10.txt
677 Bytes
Pandas, part 11 -- Memory management and categories.ipynb
97.1 KB
121 Exercises 10.mp4
2 mins
120 Avoiding low-memory warnings.mp4
4 mins
122 Exercise solutions 10.mp4
5 mins
118 Setting dtypes upon load.mp4
3 mins
119 Predefining categories.mp4
6 mins
117 Categories.mp4
8 mins
116 Memory usage in series and data frames.mp4
7 mins
115 Data frames and memory usage.mp4
13 mins