Pandas
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Section 1: Introduction
Pandas, part 1 -- introduction.ipynb
1 Introduction
2 what-is-pandas.mov
3 Installing Pandas
4 Loading Pandas into Jupyter
Section 2: Series
Pandas, part 2 -- series.ipynb
5 Creating a series
6 Creating a series with NumPy
7 Setting and retrieving with indexes
8 Retrieving with loc and iloc
9 Setting the index
10 Non-unique indexes
10a Fancy indexing
11 Basic methods
12 Operations by index
13 Broadcasting operators
14 Boolean indexing
15 Exercises 1
exercise-1.txt
16 Exercise solutions 1
Section 3: dtypes and NaN
Pandas, part 3 -- dtypes and NaN.ipynb
17 dtypes
18 assigning to dtypes
19 Using astype
20 NaN
20a Skipping NaN
21 dropna and fillna
22 fill_value
23 Exercises 2
exercise-2.txt
24 Exercise solutions 2
Section 4: Advanced series functionality
Pandas, part 4 -- advanced series.ipynb
25 size and count
26 median and quantiles
27 describe
28 describe with non-numeric data
29 head and tail
30 value_counts
31 duplicated
32 replace
33 Sorting
34 apply
35 Exercises 3
exercise-3.txt
36 Exercise solutions 3
Section 5: Strings
Pandas, part 5 -- Strings.ipynb
37 Strings in Pandas vs NumPy
38 String methods and the "str" object
39 Finding numbers
40 startswith and endswith
41 [] and strings
42 str.contains
43 find and index
44 Modifying data
45 Splitting and reusing str
46 Exercises 4
exercise-4.txt
47 Exercise 4 solutions
Section 6: Plotting series
Pandas, part 6 -- plotting.ipynb
48 Simple plots with matplotlib
49 More sophisticated plotting with M...
50 Line plots via pandas
51 Bar plots with pandas
52 Histograms
53 Pie plots
54 Box plots
55 Exercises 5
exercise-5.txt
56 Exercise 5 solutions
Section 7: Data frames
Pandas, part 7 -- data frames.ipynb
57 Data frame introduction
58 Index and columns -- simple retrie...
58a Dot syntax for column retrieval
59 Setting the index and columns
60 Retrieving an individual value
61 Creating data frames from NumPy ar...
62 Creating data frames from a list o...
63 Creating data frames from a dict o...
64 Methods on columns
65 Methods on an entire data frame
66 Retrieving multiple columns
67 Retrieving multiple rows
68 Updating values in a data frame
68a Using "describe" on data frames
68b Updating a column
68c Adding columns
68d Updating values in rows and addin...
68e Dropping one or more rows
68f Dropping one or more columns
69 Exercises 6
exercise-6.txt
70 Exercise solutions 6
Section 8: Boolean indexes and data frames
Pandas, part 8 -- boolean indexes and...
71 Boolean indexes on a column
72 Applying boolean indexes to other ...
73 Complex queries across columns
74 Applying a boolean index to an ent...
75 Assigning to data frames -- recap
76 Assigning to multiple rows and col...
77 Assigning to a column based on a b...
78 Chained assignment -- what it is, ...
79 Data frame assignment example
80 Assigning a scalar value to a data...
81 Assigning a vector value to a data...
82 Using df.replace to replace values...
82a Using isna, dropna, and fillna wi...
83 Using mask and where
84 Using clip
85 Exercises 7
exercise-7.txt
86 Exercise solutions 7
Section 9: Pandas and I/O — reading and writing files
Pandas, part 9 -- input and output.ipynb
87 Pandas and IO -- and saving to the...
88 Saving to CSV
89 Changing the CSV separator
90 NaN representation
91 Choosing output columns
92 Writing row and column names
93 Saving with compression
94 Reading CSV files
95 Choosing and ignoring header rows
96 Naming columns
97 Choosing columns
98 Choosing + naming
99 Reading NaN values
100 dtype hints when reading CSV
101 Reading from the network
102 Exercises 8
exercise-8.txt
103 Exercise 8 solutions
104 Excel files
105 JSON files
106 SQL databases
Section 10: Data analysis with Pandas
Pandas, part 10 -- analysis of real-w...
flight-delays.zip
taxi.csv
107 Analysis of taxi data
108 Taxi data part 2
109 Taxi data part 3
110 Taxi data part 4
111 Taxi data part 5
112 Taxi data part 6
113 Exercises 9
114 Exercise 9 solutions
Section 11: Memory management and categories
Pandas, part 11 -- Memory management ...
115 Data frames and memory usage
116 Memory usage in series and data f...
117 Categories.mp4
118 Setting dtypes upon load.mp4
119 Predefining categories
120 Avoiding low-memory warnings.mp4
exercise-10.txt
airlines.dat
121 Exercises 10.mp4
122 Exercise solutions 10.mp4
Section 12: Indexes and multi-indexes
Pandas, part 12 -- indexes.ipynb
123 set_index and reset_index.mp4
124 multi-indexes on series.mp4
125 multi-indexes on data frames.mp4
126 stack and unstack.mp4
127 swaplevel.mp4
128 Exercises 11.mp4
exercise-11.txt
129 Exercise solutions 11.mp4
college.csv
Section 13: Sorting, merging, and grouping
Pandas, part 13 -- sorting, joining, ...
reuven_travel.csv
oecd_locations.csv
phonecodes.json
oecd_tourist_spending.csv
weather.zip
130 sort_index.mp4
131 sort_values.mp4
132 concatenating data frames.mp4
133 concatenating different data fram...
134 Inner and outer joins.mp4
135 merging -- inner, left, right, an...
136 groupby.mp4
137 pivot tables.mp4
138 Exercises 12.mp4
exercise-12.txt
139 Exercise solutions 12.mp4
Section 14: Plotting data frames
140 Plotting data frames.mp4
141 Bar plots.mp4
142 Stacked bar plots.mp4
143 Histograms.mp4
144 Pie plots.mp4
145 Box plots.mp4
146 Scatter plots.mp4
147 Scatter plots and colormaps.mp4
148 Scatter matrix.mp4
149 Exercises 13.mp4
150 Exercise 13 solutions.mp4
exercise-13.txt
Pandas, part 14 -- plotting.ipynb
Conclusion
151 Conclusion
Products
Course
Section
Lesson
26 median and quantiles
26 median and quantiles
Pandas
Buy now
Learn more
Section 1: Introduction
Pandas, part 1 -- introduction.ipynb
1 Introduction
2 what-is-pandas.mov
3 Installing Pandas
4 Loading Pandas into Jupyter
Section 2: Series
Pandas, part 2 -- series.ipynb
5 Creating a series
6 Creating a series with NumPy
7 Setting and retrieving with indexes
8 Retrieving with loc and iloc
9 Setting the index
10 Non-unique indexes
10a Fancy indexing
11 Basic methods
12 Operations by index
13 Broadcasting operators
14 Boolean indexing
15 Exercises 1
exercise-1.txt
16 Exercise solutions 1
Section 3: dtypes and NaN
Pandas, part 3 -- dtypes and NaN.ipynb
17 dtypes
18 assigning to dtypes
19 Using astype
20 NaN
20a Skipping NaN
21 dropna and fillna
22 fill_value
23 Exercises 2
exercise-2.txt
24 Exercise solutions 2
Section 4: Advanced series functionality
Pandas, part 4 -- advanced series.ipynb
25 size and count
26 median and quantiles
27 describe
28 describe with non-numeric data
29 head and tail
30 value_counts
31 duplicated
32 replace
33 Sorting
34 apply
35 Exercises 3
exercise-3.txt
36 Exercise solutions 3
Section 5: Strings
Pandas, part 5 -- Strings.ipynb
37 Strings in Pandas vs NumPy
38 String methods and the "str" object
39 Finding numbers
40 startswith and endswith
41 [] and strings
42 str.contains
43 find and index
44 Modifying data
45 Splitting and reusing str
46 Exercises 4
exercise-4.txt
47 Exercise 4 solutions
Section 6: Plotting series
Pandas, part 6 -- plotting.ipynb
48 Simple plots with matplotlib
49 More sophisticated plotting with M...
50 Line plots via pandas
51 Bar plots with pandas
52 Histograms
53 Pie plots
54 Box plots
55 Exercises 5
exercise-5.txt
56 Exercise 5 solutions
Section 7: Data frames
Pandas, part 7 -- data frames.ipynb
57 Data frame introduction
58 Index and columns -- simple retrie...
58a Dot syntax for column retrieval
59 Setting the index and columns
60 Retrieving an individual value
61 Creating data frames from NumPy ar...
62 Creating data frames from a list o...
63 Creating data frames from a dict o...
64 Methods on columns
65 Methods on an entire data frame
66 Retrieving multiple columns
67 Retrieving multiple rows
68 Updating values in a data frame
68a Using "describe" on data frames
68b Updating a column
68c Adding columns
68d Updating values in rows and addin...
68e Dropping one or more rows
68f Dropping one or more columns
69 Exercises 6
exercise-6.txt
70 Exercise solutions 6
Section 8: Boolean indexes and data frames
Pandas, part 8 -- boolean indexes and...
71 Boolean indexes on a column
72 Applying boolean indexes to other ...
73 Complex queries across columns
74 Applying a boolean index to an ent...
75 Assigning to data frames -- recap
76 Assigning to multiple rows and col...
77 Assigning to a column based on a b...
78 Chained assignment -- what it is, ...
79 Data frame assignment example
80 Assigning a scalar value to a data...
81 Assigning a vector value to a data...
82 Using df.replace to replace values...
82a Using isna, dropna, and fillna wi...
83 Using mask and where
84 Using clip
85 Exercises 7
exercise-7.txt
86 Exercise solutions 7
Section 9: Pandas and I/O — reading and writing files
Pandas, part 9 -- input and output.ipynb
87 Pandas and IO -- and saving to the...
88 Saving to CSV
89 Changing the CSV separator
90 NaN representation
91 Choosing output columns
92 Writing row and column names
93 Saving with compression
94 Reading CSV files
95 Choosing and ignoring header rows
96 Naming columns
97 Choosing columns
98 Choosing + naming
99 Reading NaN values
100 dtype hints when reading CSV
101 Reading from the network
102 Exercises 8
exercise-8.txt
103 Exercise 8 solutions
104 Excel files
105 JSON files
106 SQL databases
Section 10: Data analysis with Pandas
Pandas, part 10 -- analysis of real-w...
flight-delays.zip
taxi.csv
107 Analysis of taxi data
108 Taxi data part 2
109 Taxi data part 3
110 Taxi data part 4
111 Taxi data part 5
112 Taxi data part 6
113 Exercises 9
114 Exercise 9 solutions
Section 11: Memory management and categories
Pandas, part 11 -- Memory management ...
115 Data frames and memory usage
116 Memory usage in series and data f...
117 Categories.mp4
118 Setting dtypes upon load.mp4
119 Predefining categories
120 Avoiding low-memory warnings.mp4
exercise-10.txt
airlines.dat
121 Exercises 10.mp4
122 Exercise solutions 10.mp4
Section 12: Indexes and multi-indexes
Pandas, part 12 -- indexes.ipynb
123 set_index and reset_index.mp4
124 multi-indexes on series.mp4
125 multi-indexes on data frames.mp4
126 stack and unstack.mp4
127 swaplevel.mp4
128 Exercises 11.mp4
exercise-11.txt
129 Exercise solutions 11.mp4
college.csv
Section 13: Sorting, merging, and grouping
Pandas, part 13 -- sorting, joining, ...
reuven_travel.csv
oecd_locations.csv
phonecodes.json
oecd_tourist_spending.csv
weather.zip
130 sort_index.mp4
131 sort_values.mp4
132 concatenating data frames.mp4
133 concatenating different data fram...
134 Inner and outer joins.mp4
135 merging -- inner, left, right, an...
136 groupby.mp4
137 pivot tables.mp4
138 Exercises 12.mp4
exercise-12.txt
139 Exercise solutions 12.mp4
Section 14: Plotting data frames
140 Plotting data frames.mp4
141 Bar plots.mp4
142 Stacked bar plots.mp4
143 Histograms.mp4
144 Pie plots.mp4
145 Box plots.mp4
146 Scatter plots.mp4
147 Scatter plots and colormaps.mp4
148 Scatter matrix.mp4
149 Exercises 13.mp4
150 Exercise 13 solutions.mp4
exercise-13.txt
Pandas, part 14 -- plotting.ipynb
Conclusion
151 Conclusion
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