Pandas by Reuven M. Lerner
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Pandas

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

This course contains 12 hours of video lessons, covering all of the aspects of Pandas you need to get up and running. Numerous exercises help to reinforce the ideas with real-world data.
Buy for $300

What's included?

Video Icon 161 videos File Icon 35 files

Contents

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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68b Updating a column.mp4
6 mins
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68c Adding columns.mp4
4 mins
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68d Updating values in rows and adding rows.mp4
3 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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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
Pandas, part 8 -- boolean indexes and data frames.ipynb
283 KB
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71 Boolean indexes on a column.mp4
4 mins
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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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83 Using mask and where .mp4
4 mins
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84 Using clip.mp4
6 mins
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85 Exercises 7.mp4
3 mins
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exercise-7.txt
1.13 KB
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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
Pandas, part 11 -- Memory management and categories.ipynb
97.1 KB
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115 Data frames and memory usage.mp4
13 mins
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116 Memory usage in series and data frames.mp4
7 mins
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117 Categories.mp4
8 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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120 Avoiding low-memory warnings.mp4
4 mins
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exercise-10.txt
677 Bytes
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airlines.dat
380 KB
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121 Exercises 10.mp4
2 mins
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122 Exercise solutions 10.mp4
5 mins
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Section 12: Indexes and multi-indexes
Pandas, part 12 -- indexes.ipynb
103 KB
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123 set_index and reset_index.mp4
7 mins
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124 multi-indexes on series.mp4
6 mins
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125 multi-indexes on data frames.mp4
5 mins
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126 stack and unstack.mp4
4 mins
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127 swaplevel.mp4
3 mins
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128 Exercises 11.mp4
3 mins
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exercise-11.txt
1.01 KB
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129 Exercise solutions 11.mp4
13 mins
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college.csv
423 KB
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Section 13: Sorting, merging, and grouping
Pandas, part 13 -- sorting, joining, merging, and grouping.ipynb
180 KB
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reuven_travel.csv
232 Bytes
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oecd_locations.csv
216 Bytes
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phonecodes.json
14.1 KB
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oecd_tourist_spending.csv
29.2 KB
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weather.zip
127 KB
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130 sort_index.mp4
6 mins
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131 sort_values.mp4
4 mins
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132 concatenating data frames.mp4
5 mins
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133 concatenating different data frames.mp4
5 mins
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134 Inner and outer joins.mp4
3 mins
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135 merging -- inner, left, right, and outer.mp4
10 mins
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136 groupby.mp4
7 mins
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137 pivot tables.mp4
3 mins
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138 Exercises 12.mp4
3 mins
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exercise-12.txt
946 Bytes
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139 Exercise solutions 12.mp4
11 mins
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Section 14: Plotting data frames
140 Plotting data frames.mp4
11 mins
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141 Bar plots.mp4
4 mins
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142 Stacked bar plots.mp4
4 mins
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143 Histograms.mp4
5 mins
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144 Pie plots.mp4
4 mins
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145 Box plots.mp4
5 mins
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146 Scatter plots.mp4
8 mins
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147 Scatter plots and colormaps.mp4
7 mins
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148 Scatter matrix.mp4
3 mins
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149 Exercises 13.mp4
2 mins
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150 Exercise 13 solutions.mp4
10 mins
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exercise-13.txt
1.04 KB
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Pandas, part 14 -- plotting.ipynb
761 KB
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Conclusion
151 Conclusion
2 mins
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