Pandas by Reuven M. Lerner
Buy for $300

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.
Buy for $300

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Video Icon 136 videos File Icon 24 files

Contents

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