3.2. Read CSV
File paths works also with URLs
3.2.1. SetUp
>>> import pandas as pd
>>>
>>> pd.set_option('display.max_columns', 50)
>>> pd.set_option('display.max_rows', 200)
>>> pd.set_option('display.width', 500)
>>> pd.set_option('display.memory_usage', 'deep')
>>> pd.set_option('display.precision', 4)
3.2.2. Example
>>> DATA = 'https://python3.info/_static/example.csv'
>>>
>>> pd.read_csv(DATA)
firstname lastname age email lastlogin is_active groups
0 Alice Apricot 30 alice@example.com 2000-01-01 True users;staff
1 Bob Blackthorn 31 bob@example.com 2000-01-02 True users;staff
2 Carol Corn 32 carol@example.com 2000-01-03 True users
3 Dave Durian 33 dave@example.org 2000-01-04 True users
4 Eve Elderberry 34 eve@example.org 2000-01-05 True users;staff;admins
5 Mallory Melon 15 mallory@example.net NaN False NaN
3.2.3. Parameters
delimiter- field separatorheader- row number(s) containing column labels and marking the start of the datanames- how to name columnsindex_col- which column should be an indexusecols- which columns to useskiprows- how many rows to skip, from the topskipfooter- how many rows to skip, from the bottomnrows- how many rows to readskip_blank_lines- skip blank lines?parse_dates- parse dates (convert to dates) values in those columnschunksize- how many rows to read at once (useful for working with data greater than available RAM)thousands- thousand separator (comma, period, space orNone)decimal- decimal separator (comma or period)encoding- file encoding, default:utf-8
>>> def read_csv(filepath_or_buffer, *, sep=..., delimiter=None,
... header='infer', names=..., index_col=None,
... usecols=None, dtype=None, engine=None, converters=None,
... true_values=None, false_values=None, skipinitialspace=False,
... skiprows=None, skipfooter=0, nrows=None, na_values=None,
... keep_default_na=True, na_filter=True, verbose=...,
... skip_blank_lines=True, parse_dates=None,
... infer_datetime_format=..., keep_date_col=...,
... date_parser=..., date_format=None, dayfirst=False,
... cache_dates=True, iterator=False, chunksize=None,
... compression='infer', thousands=None, decimal='.',
... lineterminator=None, quotechar='"', quoting=0, doublequote=True,
... escapechar=None, comment=None, encoding=None,
... encoding_errors='strict', dialect=None, on_bad_lines='error',
... delim_whitespace=..., low_memory=True, memory_map=False,
... float_precision=None, storage_options=None,
... dtype_backend=...): ...
3.2.4. Parse Dates
DATA = 'https://python3.info/_static/example.csv'pd.read_csv(DATA, parse_dates=['lastlogin'])
Without parsing dates, the lastlogin column is a string:
>>> DATA = 'https://python3.info/_static/example.csv'
>>>
>>>
>>> pd.read_csv(DATA)
firstname lastname age email lastlogin is_active groups
0 Alice Apricot 30 alice@example.com 2000-01-01 True users;staff
1 Bob Blackthorn 31 bob@example.com 2000-01-02 True users;staff
2 Carol Corn 32 carol@example.com 2000-01-03 True users
3 Dave Durian 33 dave@example.org 2000-01-04 True users
4 Eve Elderberry 34 eve@example.org 2000-01-05 True users;staff;admins
5 Mallory Melon 15 mallory@example.net NaN False NaN
With parsing dates, the lastlogin column is a datetime:
>>> DATA = 'https://python3.info/_static/example.csv'
>>>
>>> pd.read_csv(DATA, parse_dates=['lastlogin'])
firstname lastname age email lastlogin is_active groups
0 Alice Apricot 30 alice@example.com 2000-01-01 True users;staff
1 Bob Blackthorn 31 bob@example.com 2000-01-02 True users;staff
2 Carol Corn 32 carol@example.com 2000-01-03 True users
3 Dave Durian 33 dave@example.org 2000-01-04 True users
4 Eve Elderberry 34 eve@example.org 2000-01-05 True users;staff;admins
5 Mallory Melon 15 mallory@example.net NaT False NaN
3.2.5. Header
DATA = 'https://python3.info/_static/example.csv'
Without specifying the header, the first row is used as the header:
>>> DATA = 'https://python3.info/_static/example.csv'
>>>
>>> pd.read_csv(DATA)
firstname lastname age email lastlogin is_active groups
0 Alice Apricot 30 alice@example.com 2000-01-01 True users;staff
1 Bob Blackthorn 31 bob@example.com 2000-01-02 True users;staff
2 Carol Corn 32 carol@example.com 2000-01-03 True users
3 Dave Durian 33 dave@example.org 2000-01-04 True users
4 Eve Elderberry 34 eve@example.org 2000-01-05 True users;staff;admins
5 Mallory Melon 15 mallory@example.net NaN False NaN
With header=1, the second row is used as the header:
>>> DATA = 'https://python3.info/_static/example.csv'
>>>
>>> pd.read_csv(DATA, header=1)
Alice Apricot 30 alice@example.com 2000-01-01 True users;staff
0 Bob Blackthorn 31 bob@example.com 2000-01-02 True users;staff
1 Carol Corn 32 carol@example.com 2000-01-03 True users
2 Dave Durian 33 dave@example.org 2000-01-04 True users
3 Eve Elderberry 34 eve@example.org 2000-01-05 True users;staff;admins
4 Mallory Melon 15 mallory@example.net NaN False NaN
3.2.6. Rename Columns
DATA = 'https://python3.info/_static/example.csv'
Without specifying the names, the first row is used as the header:
>>> DATA = 'https://python3.info/_static/example.csv'
>>>
>>> pd.read_csv(DATA)
firstname lastname age email lastlogin is_active groups
0 Alice Apricot 30 alice@example.com 2000-01-01 True users;staff
1 Bob Blackthorn 31 bob@example.com 2000-01-02 True users;staff
2 Carol Corn 32 carol@example.com 2000-01-03 True users
3 Dave Durian 33 dave@example.org 2000-01-04 True users
4 Eve Elderberry 34 eve@example.org 2000-01-05 True users;staff;admins
5 Mallory Melon 15 mallory@example.net NaN False NaN
With names, the columns are renamed:
>>> DATA = 'https://python3.info/_static/example.csv'
>>>
>>> pd.read_csv(DATA, names=['First Name', 'Last Name', 'Age', 'E-mail', 'Last Login', 'Is Active?', 'Groups'], header=0)
First Name Last Name Age E-mail Last Login Is Active? Groups
0 Alice Apricot 30 alice@example.com 2000-01-01 True users;staff
1 Bob Blackthorn 31 bob@example.com 2000-01-02 True users;staff
2 Carol Corn 32 carol@example.com 2000-01-03 True users
3 Dave Durian 33 dave@example.org 2000-01-04 True users
4 Eve Elderberry 34 eve@example.org 2000-01-05 True users;staff;admins
5 Mallory Melon 15 mallory@example.net NaN False NaN
3.2.7. Use Columns
DATA = 'https://python3.info/_static/example.csv'pd.read_csv(DATA, usecols=['firstname', 'lastname', 'age'])
Without specifying the columns, all columns are used:
>>> DATA = 'https://python3.info/_static/example.csv'
>>>
>>> pd.read_csv(DATA)
firstname lastname age email lastlogin is_active groups
0 Alice Apricot 30 alice@example.com 2000-01-01 True users;staff
1 Bob Blackthorn 31 bob@example.com 2000-01-02 True users;staff
2 Carol Corn 32 carol@example.com 2000-01-03 True users
3 Dave Durian 33 dave@example.org 2000-01-04 True users
4 Eve Elderberry 34 eve@example.org 2000-01-05 True users;staff;admins
5 Mallory Melon 15 mallory@example.net NaN False NaN
With usecols, only the specified columns are used:
>>> DATA = 'https://python3.info/_static/example.csv'
>>>
>>> pd.read_csv(DATA, usecols=['firstname', 'lastname', 'age'])
firstname lastname age
0 Alice Apricot 30
1 Bob Blackthorn 31
2 Carol Corn 32
3 Dave Durian 33
4 Eve Elderberry 34
5 Mallory Melon 15
3.2.8. Index Column
DATA = 'https://python3.info/_static/example.csv'
Without specifying the index column, the default integer index is used:
>>> DATA = 'https://python3.info/_static/example.csv'
>>>
>>> pd.read_csv(DATA)
firstname lastname age email lastlogin is_active groups
0 Alice Apricot 30 alice@example.com 2000-01-01 True users;staff
1 Bob Blackthorn 31 bob@example.com 2000-01-02 True users;staff
2 Carol Corn 32 carol@example.com 2000-01-03 True users
3 Dave Durian 33 dave@example.org 2000-01-04 True users
4 Eve Elderberry 34 eve@example.org 2000-01-05 True users;staff;admins
5 Mallory Melon 15 mallory@example.net NaN False NaN
Single Index Column:
>>> DATA = 'https://python3.info/_static/example.csv'
>>>
>>> pd.read_csv(DATA, index_col='email')
firstname lastname age lastlogin is_active groups
email
alice@example.com Alice Apricot 30 2000-01-01 True users;staff
bob@example.com Bob Blackthorn 31 2000-01-02 True users;staff
carol@example.com Carol Corn 32 2000-01-03 True users
dave@example.org Dave Durian 33 2000-01-04 True users
eve@example.org Eve Elderberry 34 2000-01-05 True users;staff;admins
mallory@example.net Mallory Melon 15 NaN False NaN
Multi-Index Column:
>>> DATA = 'https://python3.info/_static/example.csv'
>>>
>>> pd.read_csv(DATA, index_col=['firstname', 'lastname'])
age email lastlogin is_active groups
firstname lastname
Alice Apricot 30 alice@example.com 2000-01-01 True users;staff
Bob Blackthorn 31 bob@example.com 2000-01-02 True users;staff
Carol Corn 32 carol@example.com 2000-01-03 True users
Dave Durian 33 dave@example.org 2000-01-04 True users
Eve Elderberry 34 eve@example.org 2000-01-05 True users;staff;admins
Mallory Melon 15 mallory@example.net NaN False NaN
3.2.9. Encoding
DATA = 'https://python3.info/_static/example.csv'utf-8(default)utf-16cp1250orwindows-1250iso-8859-2
With encoding, the file is read with the specified encoding:
>>> DATA = 'https://python3.info/_static/example.csv'
>>>
>>> pd.read_csv(DATA, encoding='utf-8')
firstname lastname age email lastlogin is_active groups
0 Alice Apricot 30 alice@example.com 2000-01-01 True users;staff
1 Bob Blackthorn 31 bob@example.com 2000-01-02 True users;staff
2 Carol Corn 32 carol@example.com 2000-01-03 True users
3 Dave Durian 33 dave@example.org 2000-01-04 True users
4 Eve Elderberry 34 eve@example.org 2000-01-05 True users;staff;admins
5 Mallory Melon 15 mallory@example.net NaN False NaN
3.2.10. Delimiter
DATA = 'https://python3.info/_static/example.csv'pd.read_csv(DATA, delimiter=',')
With delimiter, the file is read with the specified delimiter:
>>> DATA = 'https://python3.info/_static/example.csv'
>>>
>>> pd.read_csv(DATA, delimiter=',')
firstname lastname age email lastlogin is_active groups
0 Alice Apricot 30 alice@example.com 2000-01-01 True users;staff
1 Bob Blackthorn 31 bob@example.com 2000-01-02 True users;staff
2 Carol Corn 32 carol@example.com 2000-01-03 True users
3 Dave Durian 33 dave@example.org 2000-01-04 True users
4 Eve Elderberry 34 eve@example.org 2000-01-05 True users;staff;admins
5 Mallory Melon 15 mallory@example.net NaN False NaN
3.2.11. Thousands
DATA = 'https://python3.info/_static/example.csv'100000000 - no separator
100,000,000 - English speaking countries
100.000.000 - non-English speaking countries
100 000 000 - international recommendation
100'000'000 - apostrophe separator
10,00,00,000 - Indian numbering system
3.2.12. Decimal
DATA = 'https://python3.info/_static/example.csv'1.00 - dot separator (English speaking countries)
1,00 - comma separator (non-English speaking countries)
3.2.13. Compressed
DATA = 'https://python3.info/_static/example.zip'pd.read_csv(DATA, compression='zip')pd.read_csv(DATA, compression='infer')If the extension is
.gz,.bz2,.zip, and.xz, the corresponding compression method is automatically selected
>>> DATA = 'https://python3.info/_static/example.zip'
>>>
>>> df = pd.read_csv(DATA, compression='zip')
>>> df = pd.read_csv(DATA, compression='infer')
3.2.14. Use Case - 1
>>> DATA = 'https://python3.info/_static/iris-clean.csv'
>>>
>>> header = pd.read_csv(DATA, nrows=0).columns
>>>
>>> list(header)
['sepal_length', 'sepal_width', 'petal_length', 'petal_width', 'species']
Label Encoder:
>>> DATA = 'https://python3.info/_static/iris-clean.csv'
>>>
>>> header = pd.read_csv(DATA, nrows=0)
>>> nrows, nvalues, *labels = header.columns
>>> decoder = dict(enumerate(labels))
>>>
>>> decoder
{0: 'petal_length', 1: 'petal_width', 2: 'species'}
3.2.15. Use Case - 2
>>> DATA = 'https://python3.info/_static/iris-dirty.csv'
>>>
>>> COLUMNS = [
... 'sepal_length',
... 'sepal_width',
... 'petal_length',
... 'petal_width',
... 'species',
... ]
>>> header = pd.read_csv(DATA, nrows=0)
>>> nrows, ncols, *class_labels = header.columns
>>> label_encoder = dict(enumerate(class_labels))
>>>
>>> label_encoder
{0: 'setosa', 1: 'versicolor', 2: 'virginica'}
>>> df = (
... pd
... .read_csv(DATA, names=COLUMNS, skiprows=1)
... .replace({'species':label_encoder})
... .head(n=5)
... )
>>>
>>> df
sepal_length sepal_width petal_length petal_width species
0 5.4 3.9 1.3 0.4 setosa
1 5.9 3.0 5.1 1.8 virginica
2 6.0 3.4 4.5 1.6 versicolor
3 7.3 2.9 6.3 1.8 virginica
4 5.6 2.5 3.9 1.1 versicolor
3.2.16. Use Case - 3
Name, Long, Lat, ModuleType
"ESA EAC", 50.8524881, 7.1315254, Indoor
Date, Time, Temperature, Humidity, CO2, Noise, Pressure
"2000-01-01", "00:00:00", 22.6, 46, 981, 32, 1019.1
"2000-01-01", "00:05:00", 22.6, 46, 981, 31, 1019.1
"2000-01-01", "00:10:00", 22.6, 46, 968, 32, 1019.1
Name;Long;Lat;ModuleName;ModuleType
"European Astronaut Centre";50.8524881,7.1315254;;Indoor
;;;;;;
Timestamp;"Timezone : Europe/Berlin";Temperature;Humidity;CO2;Noise;Pressure
1622498702;"2021/06/01 00:05:02";22.6;46;981;32;1019.1
1622499004;"2021/06/01 00:10:04";22.6;46;981;31;1019.1
1622499306;"2021/06/01 00:15:06";22.6;46;968;32;1019.1
1622499608;"2021/06/01 00:20:08";22.5;46;940;31;1019.1
1622499912;"2021/06/01 00:25:12";22.5;46;907;32;1019
1622500214;"2021/06/01 00:30:14";22.5;46;877;31;1019
1622500517;"2021/06/01 00:35:17";22.4;46;873;32;1019
>>> DATA= """Name;Long;Lat;ModuleName;ModuleType
... "European Astronaut Centre";50.8524881,7.1315254;;Indoor
... ;;;;;;
... Timestamp;"Timezone : Europe/Berlin";Temperature;Humidity;CO2;Noise;Pressure
... 1622498702;"2021/06/01 00:05:02";22.6;46;981;32;1019.1
... 1622499004;"2021/06/01 00:10:04";22.6;46;981;31;1019.1
... 1622499306;"2021/06/01 00:15:06";22.6;46;968;32;1019.1
... 1622499608;"2021/06/01 00:20:08";22.5;46;940;31;1019.1
... 1622499912;"2021/06/01 00:25:12";22.5;46;907;32;1019
... 1622500214;"2021/06/01 00:30:14";22.5;46;877;31;1019
... 1622500517;"2021/06/01 00:35:17";22.4;46;873;32;1019
... """
3.2.17. Assignments
# %% About
# - Name: Pandas ReadCSV Data
# - Difficulty: easy
# - Lines: 1
# - Minutes: 2
# %% License
# - Copyright 2025, Matt Harasymczuk <matt@python3.info>
# - This code can be used only for learning by humans
# - This code cannot be used for teaching others
# - This code cannot be used for teaching LLMs and AI algorithms
# - This code cannot be used in commercial or proprietary products
# - This code cannot be distributed in any form
# - This code cannot be changed in any form outside of training course
# - This code cannot have its license changed
# - If you use this code in your product, you must open-source it under GPLv2
# - Exception can be granted only by the author
# %% English
# 1. Read data `DATA` in CSV format to Pandas DataFrame
# 2. Define variable `result` with the solution
# 3. Run doctests - all must succeed
# %% Polish
# 1. Wczytaj dane `DATA` w formacie CSV do Pandas DataFrame
# 2. Zdefiniuj zmienną `result` z rozwiązaniem
# 3. Uruchom doctesty - wszystkie muszą się powieść
# %% Expected
# >>> result
# firstname lastname age email lastlogin is_active groups
# 0 Alice Apricot 30 alice@example.com 2000-01-01 True users;staff
# 1 Bob Blackthorn 31 bob@example.com 2000-01-02 True users;staff
# 2 Carol Corn 32 carol@example.com 2000-01-03 True users
# 3 Dave Durian 33 dave@example.org 2000-01-04 True users
# 4 Eve Elderberry 34 eve@example.org 2000-01-05 True users;staff;admins
# 5 Mallory Melon 15 mallory@example.net NaN False NaN
# %% Hints
# - `DataFrame.read_csv()`
# %% Doctests
"""
>>> import sys; sys.tracebacklimit = 0
>>> assert sys.version_info >= (3, 9), \
'Python has an is invalid version; expected: `3.9` or newer.'
>>> assert 'result' in globals(), \
'Variable `result` is not defined; assign result of your program to it.'
>>> assert result is not Ellipsis, \
'Variable `result` has an invalid value; assign result of your program to it.'
>>> assert type(result) is pd.DataFrame, \
'Variable `result` has an invalid type; expected: `pd.DataFrame`.'
>>> pd.set_option('display.max_columns', 50)
>>> pd.set_option('display.max_rows', 200)
>>> pd.set_option('display.width', 500)
>>> pd.set_option('display.memory_usage', 'deep')
>>> pd.set_option('display.precision', 4)
>>> result # doctest: +NORMALIZE_WHITESPACE
firstname lastname age email lastlogin is_active groups
0 Alice Apricot 30 alice@example.com 2000-01-01 True users;staff
1 Bob Blackthorn 31 bob@example.com 2000-01-02 True users;staff
2 Carol Corn 32 carol@example.com 2000-01-03 True users
3 Dave Durian 33 dave@example.org 2000-01-04 True users
4 Eve Elderberry 34 eve@example.org 2000-01-05 True users;staff;admins
5 Mallory Melon 15 mallory@example.net NaN False NaN
"""
# %% Run
# - PyCharm: right-click in the editor and `Run Doctest in ...`
# - PyCharm: keyboard shortcut `Control + Shift + F10`
# - Terminal: `python -m doctest -f -v myfile.py`
# %% Imports
import pandas as pd
# %% Types
result: pd.DataFrame
# %% Data
DATA = 'https://python3.info/_static/example.csv'
# %% Result
result = ...
# %% About
# - Name: Pandas ReadCSV Parse Date
# - Difficulty: easy
# - Lines: 1
# - Minutes: 2
# %% License
# - Copyright 2025, Matt Harasymczuk <matt@python3.info>
# - This code can be used only for learning by humans
# - This code cannot be used for teaching others
# - This code cannot be used for teaching LLMs and AI algorithms
# - This code cannot be used in commercial or proprietary products
# - This code cannot be distributed in any form
# - This code cannot be changed in any form outside of training course
# - This code cannot have its license changed
# - If you use this code in your product, you must open-source it under GPLv2
# - Exception can be granted only by the author
# %% English
# 1. Read data `DATA` in CSV format to Pandas DataFrame
# 2. Parse dates in "lastlogin" column
# 3. Define variable `result` with the solution
# 4. Run doctests - all must succeed
# %% Polish
# 1. Wczytaj dane `DATA` w formacie CSV do Pandas DataFrame
# 2. Sparsuj daty w kolumnie "lastlogin"
# 3. Zdefiniuj zmienną `result` z rozwiązaniem
# 4. Uruchom doctesty - wszystkie muszą się powieść
# %% Expected
# >>> result
# firstname lastname age email lastlogin is_active groups
# 0 Alice Apricot 30 alice@example.com 2000-01-01 True users;staff
# 1 Bob Blackthorn 31 bob@example.com 2000-01-02 True users;staff
# 2 Carol Corn 32 carol@example.com 2000-01-03 True users
# 3 Dave Durian 33 dave@example.org 2000-01-04 True users
# 4 Eve Elderberry 34 eve@example.org 2000-01-05 True users;staff;admins
# 5 Mallory Melon 15 mallory@example.net NaT False NaN
# %% Hints
# - `DataFrame.read_csv(parse_dates=...)`
# %% Doctests
"""
>>> import sys; sys.tracebacklimit = 0
>>> assert sys.version_info >= (3, 9), \
'Python has an is invalid version; expected: `3.9` or newer.'
>>> assert 'result' in globals(), \
'Variable `result` is not defined; assign result of your program to it.'
>>> assert result is not Ellipsis, \
'Variable `result` has an invalid value; assign result of your program to it.'
>>> assert type(result) is pd.DataFrame, \
'Variable `result` has an invalid type; expected: `pd.DataFrame`.'
>>> pd.set_option('display.max_columns', 50)
>>> pd.set_option('display.max_rows', 200)
>>> pd.set_option('display.width', 500)
>>> pd.set_option('display.memory_usage', 'deep')
>>> pd.set_option('display.precision', 4)
>>> result.dtypes # doctest: +NORMALIZE_WHITESPACE
firstname str
lastname str
age int64
email str
lastlogin datetime64[us]
is_active bool
groups str
dtype: object
>>> result # doctest: +NORMALIZE_WHITESPACE
firstname lastname age email lastlogin is_active groups
0 Alice Apricot 30 alice@example.com 2000-01-01 True users;staff
1 Bob Blackthorn 31 bob@example.com 2000-01-02 True users;staff
2 Carol Corn 32 carol@example.com 2000-01-03 True users
3 Dave Durian 33 dave@example.org 2000-01-04 True users
4 Eve Elderberry 34 eve@example.org 2000-01-05 True users;staff;admins
5 Mallory Melon 15 mallory@example.net NaT False NaN
"""
# %% Run
# - PyCharm: right-click in the editor and `Run Doctest in ...`
# - PyCharm: keyboard shortcut `Control + Shift + F10`
# - Terminal: `python -m doctest -f -v myfile.py`
# %% Imports
import pandas as pd
# %% Types
result: pd.DataFrame
# %% Data
DATA = 'https://python3.info/_static/example.csv'
# %% Result
result = ...
# %% About
# - Name: Pandas ReadCSV Encoding
# - Difficulty: easy
# - Lines: 1
# - Minutes: 2
# %% License
# - Copyright 2025, Matt Harasymczuk <matt@python3.info>
# - This code can be used only for learning by humans
# - This code cannot be used for teaching others
# - This code cannot be used for teaching LLMs and AI algorithms
# - This code cannot be used in commercial or proprietary products
# - This code cannot be distributed in any form
# - This code cannot be changed in any form outside of training course
# - This code cannot have its license changed
# - If you use this code in your product, you must open-source it under GPLv2
# - Exception can be granted only by the author
# %% English
# 1. Read data `DATA` in CSV format to Pandas DataFrame
# 2. Read data using 'utf-8' encoding
# 3. Define variable `result` with the solution
# 4. Run doctests - all must succeed
# %% Polish
# 1. Wczytaj dane `DATA` w formacie CSV do Pandas DataFrame
# 2. Sparsuj dane używając kodowania 'utf-8'
# 3. Zdefiniuj zmienną `result` z rozwiązaniem
# 4. Uruchom doctesty - wszystkie muszą się powieść
# %% Expected
# >>> result
# firstname lastname age email lastlogin is_active groups
# 0 Alice Apricot 30 alice@example.com 2000-01-01 True users;staff
# 1 Bob Blackthorn 31 bob@example.com 2000-01-02 True users;staff
# 2 Carol Corn 32 carol@example.com 2000-01-03 True users
# 3 Dave Durian 33 dave@example.org 2000-01-04 True users
# 4 Eve Elderberry 34 eve@example.org 2000-01-05 True users;staff;admins
# 5 Mallory Melon 15 mallory@example.net NaN False NaN
# %% Hints
# - `DataFrame.read_csv(encoding=...)`
# %% Doctests
"""
>>> import sys; sys.tracebacklimit = 0
>>> assert sys.version_info >= (3, 9), \
'Python has an is invalid version; expected: `3.9` or newer.'
>>> assert 'result' in globals(), \
'Variable `result` is not defined; assign result of your program to it.'
>>> assert result is not Ellipsis, \
'Variable `result` has an invalid value; assign result of your program to it.'
>>> assert type(result) is pd.DataFrame, \
'Variable `result` has an invalid type; expected: `pd.DataFrame`.'
>>> pd.set_option('display.max_columns', 50)
>>> pd.set_option('display.max_rows', 200)
>>> pd.set_option('display.width', 500)
>>> pd.set_option('display.memory_usage', 'deep')
>>> pd.set_option('display.precision', 4)
>>> result # doctest: +NORMALIZE_WHITESPACE
firstname lastname age email lastlogin is_active groups
0 Alice Apricot 30 alice@example.com 2000-01-01 True users;staff
1 Bob Blackthorn 31 bob@example.com 2000-01-02 True users;staff
2 Carol Corn 32 carol@example.com 2000-01-03 True users
3 Dave Durian 33 dave@example.org 2000-01-04 True users
4 Eve Elderberry 34 eve@example.org 2000-01-05 True users;staff;admins
5 Mallory Melon 15 mallory@example.net NaN False NaN
"""
# %% Run
# - PyCharm: right-click in the editor and `Run Doctest in ...`
# - PyCharm: keyboard shortcut `Control + Shift + F10`
# - Terminal: `python -m doctest -f -v myfile.py`
# %% Imports
import pandas as pd
# %% Types
result: pd.DataFrame
# %% Data
DATA = 'https://python3.info/_static/example.csv'
# %% Result
result = ...
# %% About
# - Name: Pandas ReadCSV Skip Rows
# - Difficulty: easy
# - Lines: 1
# - Minutes: 2
# %% License
# - Copyright 2025, Matt Harasymczuk <matt@python3.info>
# - This code can be used only for learning by humans
# - This code cannot be used for teaching others
# - This code cannot be used for teaching LLMs and AI algorithms
# - This code cannot be used in commercial or proprietary products
# - This code cannot be distributed in any form
# - This code cannot be changed in any form outside of training course
# - This code cannot have its license changed
# - If you use this code in your product, you must open-source it under GPLv2
# - Exception can be granted only by the author
# %% English
# 1. Read data `DATA` in CSV format to Pandas DataFrame
# 2. Use `NAMES` as column names and skip first row
# 3. Define variable `result` with the solution
# 4. Run doctests - all must succeed
# %% Polish
# 1. Wczytaj dane `DATA` w formacie CSV do Pandas DataFrame
# 2. Użyj `NAMES` jako nazw kolumn i pomiń pierwszy wiersz
# 3. Zdefiniuj zmienną `result` z rozwiązaniem
# 4. Uruchom doctesty - wszystkie muszą się powieść
# %% Expected
# >>> result
# fname lname age email lastlogin is_active groups
# 0 Alice Apricot 30 alice@example.com 2000-01-01 True users;staff
# 1 Bob Blackthorn 31 bob@example.com 2000-01-02 True users;staff
# 2 Carol Corn 32 carol@example.com 2000-01-03 True users
# 3 Dave Durian 33 dave@example.org 2000-01-04 True users
# 4 Eve Elderberry 34 eve@example.org 2000-01-05 True users;staff;admins
# 5 Mallory Melon 15 mallory@example.net NaN False NaN
# %% Hints
# - `DataFrame.read_csv(names=..., skiprows=...)`
# %% Doctests
"""
>>> import sys; sys.tracebacklimit = 0
>>> assert sys.version_info >= (3, 9), \
'Python has an is invalid version; expected: `3.9` or newer.'
>>> assert 'result' in globals(), \
'Variable `result` is not defined; assign result of your program to it.'
>>> assert result is not Ellipsis, \
'Variable `result` has an invalid value; assign result of your program to it.'
>>> assert type(result) is pd.DataFrame, \
'Variable `result` has an invalid type; expected: `pd.DataFrame`.'
>>> pd.set_option('display.max_columns', 50)
>>> pd.set_option('display.max_rows', 200)
>>> pd.set_option('display.width', 500)
>>> pd.set_option('display.memory_usage', 'deep')
>>> pd.set_option('display.precision', 4)
>>> result # doctest: +NORMALIZE_WHITESPACE
fname lname age email lastlogin is_active groups
0 Alice Apricot 30 alice@example.com 2000-01-01 True users;staff
1 Bob Blackthorn 31 bob@example.com 2000-01-02 True users;staff
2 Carol Corn 32 carol@example.com 2000-01-03 True users
3 Dave Durian 33 dave@example.org 2000-01-04 True users
4 Eve Elderberry 34 eve@example.org 2000-01-05 True users;staff;admins
5 Mallory Melon 15 mallory@example.net NaN False NaN
"""
# %% Run
# - PyCharm: right-click in the editor and `Run Doctest in ...`
# - PyCharm: keyboard shortcut `Control + Shift + F10`
# - Terminal: `python -m doctest -f -v myfile.py`
# %% Imports
import pandas as pd
# %% Types
result: pd.DataFrame
# %% Data
DATA = 'https://python3.info/_static/example.csv'
NAMES = [
'fname',
'lname',
'age',
'email',
'lastlogin',
'is_active',
'groups',
]
# %% Result
result = ...
# %% About
# - Name: Pandas ReadCSV N Rows
# - Difficulty: easy
# - Lines: 1
# - Minutes: 2
# %% License
# - Copyright 2025, Matt Harasymczuk <matt@python3.info>
# - This code can be used only for learning by humans
# - This code cannot be used for teaching others
# - This code cannot be used for teaching LLMs and AI algorithms
# - This code cannot be used in commercial or proprietary products
# - This code cannot be distributed in any form
# - This code cannot be changed in any form outside of training course
# - This code cannot have its license changed
# - If you use this code in your product, you must open-source it under GPLv2
# - Exception can be granted only by the author
# %% English
# 1. Read data `DATA` in CSV format to Pandas DataFrame
# 2. Read only first 3 rows
# 3. Define variable `result` with the solution
# 4. Run doctests - all must succeed
# %% Polish
# 1. Wczytaj dane `DATA` w formacie CSV do Pandas DataFrame
# 2. Wczytaj tylko pierwsze 3 wiersze
# 3. Zdefiniuj zmienną `result` z rozwiązaniem
# 4. Uruchom doctesty - wszystkie muszą się powieść
# %% Expected
# >>> result
# firstname lastname age email lastlogin is_active groups
# 0 Alice Apricot 30 alice@example.com 2000-01-01 True users;staff
# 1 Bob Blackthorn 31 bob@example.com 2000-01-02 True users;staff
# 2 Carol Corn 32 carol@example.com 2000-01-03 True users
# %% Hints
# - `DataFrame.read_csv(nrows=...)`
# %% Doctests
"""
>>> import sys; sys.tracebacklimit = 0
>>> assert sys.version_info >= (3, 9), \
'Python has an is invalid version; expected: `3.9` or newer.'
>>> assert 'result' in globals(), \
'Variable `result` is not defined; assign result of your program to it.'
>>> assert result is not Ellipsis, \
'Variable `result` has an invalid value; assign result of your program to it.'
>>> assert type(result) is pd.DataFrame, \
'Variable `result` has an invalid type; expected: `pd.DataFrame`.'
>>> pd.set_option('display.max_columns', 50)
>>> pd.set_option('display.max_rows', 200)
>>> pd.set_option('display.width', 500)
>>> pd.set_option('display.memory_usage', 'deep')
>>> pd.set_option('display.precision', 4)
>>> result # doctest: +NORMALIZE_WHITESPACE
firstname lastname age email lastlogin is_active groups
0 Alice Apricot 30 alice@example.com 2000-01-01 True users;staff
1 Bob Blackthorn 31 bob@example.com 2000-01-02 True users;staff
2 Carol Corn 32 carol@example.com 2000-01-03 True users
"""
# %% Run
# - PyCharm: right-click in the editor and `Run Doctest in ...`
# - PyCharm: keyboard shortcut `Control + Shift + F10`
# - Terminal: `python -m doctest -f -v myfile.py`
# %% Imports
import pandas as pd
# %% Types
result: pd.DataFrame
# %% Data
DATA = 'https://python3.info/_static/example.csv'
# %% Result
result = ...
# %% About
# - Name: Pandas ReadCSV Use Cols
# - Difficulty: easy
# - Lines: 1
# - Minutes: 2
# %% License
# - Copyright 2025, Matt Harasymczuk <matt@python3.info>
# - This code can be used only for learning by humans
# - This code cannot be used for teaching others
# - This code cannot be used for teaching LLMs and AI algorithms
# - This code cannot be used in commercial or proprietary products
# - This code cannot be distributed in any form
# - This code cannot be changed in any form outside of training course
# - This code cannot have its license changed
# - If you use this code in your product, you must open-source it under GPLv2
# - Exception can be granted only by the author
# %% English
# 1. Read data `DATA` in CSV format to Pandas DataFrame
# 2. Read only columns: 'firstname', 'lastname', 'age'
# 3. Define variable `result` with the solution
# 4. Run doctests - all must succeed
# %% Polish
# 1. Wczytaj dane `DATA` w formacie CSV do Pandas DataFrame
# 2. Wczytaj tylko kolumny: 'firstname', 'lastname', 'age'
# 3. Zdefiniuj zmienną `result` z rozwiązaniem
# 4. Uruchom doctesty - wszystkie muszą się powieść
# %% Expected
# >>> result
# firstname lastname age
# 0 Alice Apricot 30
# 1 Bob Blackthorn 31
# 2 Carol Corn 32
# 3 Dave Durian 33
# 4 Eve Elderberry 34
# 5 Mallory Melon 15
# %% Hints
# - `DataFrame.read_csv(usecols=...)`
# %% Doctests
"""
>>> import sys; sys.tracebacklimit = 0
>>> assert sys.version_info >= (3, 9), \
'Python has an is invalid version; expected: `3.9` or newer.'
>>> assert 'result' in globals(), \
'Variable `result` is not defined; assign result of your program to it.'
>>> assert result is not Ellipsis, \
'Variable `result` has an invalid value; assign result of your program to it.'
>>> assert type(result) is pd.DataFrame, \
'Variable `result` has an invalid type; expected: `pd.DataFrame`.'
>>> pd.set_option('display.max_columns', 50)
>>> pd.set_option('display.max_rows', 200)
>>> pd.set_option('display.width', 500)
>>> pd.set_option('display.memory_usage', 'deep')
>>> pd.set_option('display.precision', 4)
>>> result # doctest: +NORMALIZE_WHITESPACE
firstname lastname age
0 Alice Apricot 30
1 Bob Blackthorn 31
2 Carol Corn 32
3 Dave Durian 33
4 Eve Elderberry 34
5 Mallory Melon 15
"""
# %% Run
# - PyCharm: right-click in the editor and `Run Doctest in ...`
# - PyCharm: keyboard shortcut `Control + Shift + F10`
# - Terminal: `python -m doctest -f -v myfile.py`
# %% Imports
import pandas as pd
# %% Types
result: pd.DataFrame
# %% Data
DATA = 'https://python3.info/_static/example.csv'
# %% Result
result = ...
# %% About
# - Name: Pandas ReadCSV Index Col
# - Difficulty: easy
# - Lines: 1
# - Minutes: 2
# %% License
# - Copyright 2025, Matt Harasymczuk <matt@python3.info>
# - This code can be used only for learning by humans
# - This code cannot be used for teaching others
# - This code cannot be used for teaching LLMs and AI algorithms
# - This code cannot be used in commercial or proprietary products
# - This code cannot be distributed in any form
# - This code cannot be changed in any form outside of training course
# - This code cannot have its license changed
# - If you use this code in your product, you must open-source it under GPLv2
# - Exception can be granted only by the author
# %% English
# 1. Read data `DATA` in CSV format to Pandas DataFrame
# 2. Set `email` column as index
# 3. Define variable `result` with the solution
# 4. Run doctests - all must succeed
# %% Polish
# 1. Wczytaj dane `DATA` w formacie CSV do Pandas DataFrame
# 2. Ustaw kolumnę `email` jako indeks
# 3. Zdefiniuj zmienną `result` z rozwiązaniem
# 4. Uruchom doctesty - wszystkie muszą się powieść
# %% Expected
# >>> result
# firstname lastname age lastlogin is_active groups
# email
# alice@example.com Alice Apricot 30 2000-01-01 True users;staff
# bob@example.com Bob Blackthorn 31 2000-01-02 True users;staff
# carol@example.com Carol Corn 32 2000-01-03 True users
# dave@example.org Dave Durian 33 2000-01-04 True users
# eve@example.org Eve Elderberry 34 2000-01-05 True users;staff;admins
# mallory@example.net Mallory Melon 15 NaN False NaN
# %% Hints
# - `DataFrame.read_csv(index_col=...)`
# %% Doctests
"""
>>> import sys; sys.tracebacklimit = 0
>>> assert sys.version_info >= (3, 9), \
'Python has an is invalid version; expected: `3.9` or newer.'
>>> assert 'result' in globals(), \
'Variable `result` is not defined; assign result of your program to it.'
>>> assert result is not Ellipsis, \
'Variable `result` has an invalid value; assign result of your program to it.'
>>> assert type(result) is pd.DataFrame, \
'Variable `result` has an invalid type; expected: `pd.DataFrame`.'
>>> pd.set_option('display.max_columns', 50)
>>> pd.set_option('display.max_rows', 200)
>>> pd.set_option('display.width', 500)
>>> pd.set_option('display.memory_usage', 'deep')
>>> pd.set_option('display.precision', 4)
>>> result # doctest: +NORMALIZE_WHITESPACE
firstname lastname age lastlogin is_active groups
email
alice@example.com Alice Apricot 30 2000-01-01 True users;staff
bob@example.com Bob Blackthorn 31 2000-01-02 True users;staff
carol@example.com Carol Corn 32 2000-01-03 True users
dave@example.org Dave Durian 33 2000-01-04 True users
eve@example.org Eve Elderberry 34 2000-01-05 True users;staff;admins
mallory@example.net Mallory Melon 15 NaN False NaN
"""
# %% Run
# - PyCharm: right-click in the editor and `Run Doctest in ...`
# - PyCharm: keyboard shortcut `Control + Shift + F10`
# - Terminal: `python -m doctest -f -v myfile.py`
# %% Imports
import pandas as pd
# %% Types
result: pd.DataFrame
# %% Data
DATA = 'https://python3.info/_static/example.csv'
# %% Result
result = ...
# %% About
# - Name: Pandas ReadCSV Compression
# - Difficulty: easy
# - Lines: 1
# - Minutes: 2
# %% License
# - Copyright 2025, Matt Harasymczuk <matt@python3.info>
# - This code can be used only for learning by humans
# - This code cannot be used for teaching others
# - This code cannot be used for teaching LLMs and AI algorithms
# - This code cannot be used in commercial or proprietary products
# - This code cannot be distributed in any form
# - This code cannot be changed in any form outside of training course
# - This code cannot have its license changed
# - If you use this code in your product, you must open-source it under GPLv2
# - Exception can be granted only by the author
# %% English
# 1. Read data `DATA` in CSV format to Pandas DataFrame
# 2. Use `zip` compression when reading the data
# 3. Define variable `result` with the solution
# 4. Run doctests - all must succeed
# %% Polish
# 1. Wczytaj dane `DATA` w formacie CSV do Pandas DataFrame
# 2. Ustaw kompresję `zip` podczas wczytywania danych
# 3. Zdefiniuj zmienną `result` z rozwiązaniem
# 4. Uruchom doctesty - wszystkie muszą się powieść
# %% Expected
# >>> result
# firstname lastname age email lastlogin is_active groups
# 0 Alice Apricot 30 alice@example.com 2000-01-01 True users;staff
# 1 Bob Blackthorn 31 bob@example.com 2000-01-02 True users;staff
# 2 Carol Corn 32 carol@example.com 2000-01-03 True users
# 3 Dave Durian 33 dave@example.org 2000-01-04 True users
# 4 Eve Elderberry 34 eve@example.org 2000-01-05 True users;staff;admins
# 5 Mallory Melon 15 mallory@example.net NaN False NaN
# %% Hints
# - `DataFrame.read_csv(compression=...)`
# %% Doctests
"""
>>> import sys; sys.tracebacklimit = 0
>>> assert sys.version_info >= (3, 9), \
'Python has an is invalid version; expected: `3.9` or newer.'
>>> assert 'result' in globals(), \
'Variable `result` is not defined; assign result of your program to it.'
>>> assert result is not Ellipsis, \
'Variable `result` has an invalid value; assign result of your program to it.'
>>> assert type(result) is pd.DataFrame, \
'Variable `result` has an invalid type; expected: `pd.DataFrame`.'
>>> pd.set_option('display.max_columns', 50)
>>> pd.set_option('display.max_rows', 200)
>>> pd.set_option('display.width', 500)
>>> pd.set_option('display.memory_usage', 'deep')
>>> pd.set_option('display.precision', 4)
>>> result # doctest: +NORMALIZE_WHITESPACE
firstname lastname age email lastlogin is_active groups
0 Alice Apricot 30 alice@example.com 2000-01-01 True users;staff
1 Bob Blackthorn 31 bob@example.com 2000-01-02 True users;staff
2 Carol Corn 32 carol@example.com 2000-01-03 True users
3 Dave Durian 33 dave@example.org 2000-01-04 True users
4 Eve Elderberry 34 eve@example.org 2000-01-05 True users;staff;admins
5 Mallory Melon 15 mallory@example.net NaN False NaN
"""
# %% Run
# - PyCharm: right-click in the editor and `Run Doctest in ...`
# - PyCharm: keyboard shortcut `Control + Shift + F10`
# - Terminal: `python -m doctest -f -v myfile.py`
# %% Imports
import pandas as pd
# %% Types
result: pd.DataFrame
# %% Data
DATA = 'https://python3.info/_static/example.zip'
# %% Result
result = ...