This introduction to pandas is derived from Data School's pandas Q&A with my own notes and code.

Changing display options in pandas¶

import pandas as pd

url = 'http://bit.ly/drinksbycountry'
drinks = pd.read_csv(url)

# this shows only the first and last 30 rows
drinks

ROWS

# to show all rows go to the documentation Pandas.get_option

# use display.max_rows
# this is the default
pd.get_option('display.max_rows')

60

# let's change to set_option to change
# be careful if you've many rows
pd.set_option('display.max_rows', None)

drinks

# reset back to normal
pd.reset_option('display.max_rows')

drinks

COLUMNS

# the default for columns is 20
pd.get_option('display.max_columns')

20

CELLS

url = 'http://bit.ly/kaggletrain'
train = pd.read_csv(url)
train.head()
# in each cell, you can see '...'
# how do we change this?

pd.get_option('display.max_colwidth')

50

# you can't use none here
pd.set_option('display.max_colwidth', 1000)

train.head()

# decimal places for numbers
pd.get_option('display.precision')

2

pd.set_option('display.precision', 3)

train.head()

drinks.head()

drinks['x'] = drinks.wine_servings * 1000

drinks['y'] = drinks.total_litres_of_pure_alcohol * 1000

drinks.head()

# split numbers using commas
pd.set_option('display.float_format', '{:,}'.format)

drinks.head()

drinks.dtypes
# this only affected y because x is int type

country                          object
beer_servings                     int64
spirit_servings                   int64
wine_servings                     int64
total_litres_of_pure_alcohol    float64
continent                        object
x                                 int64
y                               float64
dtype: object

# we can convert y to float using .astype
# replace existing column using assignment
drinks['wine_servings'] = drinks.wine_servings.astype(float)

# we need to concatenate
drinks.dtypes

country                          object
beer_servings                     int64
spirit_servings                   int64
wine_servings                   float64
total_litres_of_pure_alcohol    float64
continent                        object
x                                 int64
y                               float64
dtype: object

# run code again
drinks['x'] = drinks.wine_servings * 1000

drinks.head()
# it works now!

# offline documentation
pd.describe_option()

display.chop_threshold : float or None
    if set to a float value, all float values smaller then the given threshold
    will be displayed as exactly 0 by repr and friends.
    [default: None] [currently: None]

display.colheader_justify : 'left'/'right'
    Controls the justification of column headers. used by DataFrameFormatter.
    [default: right] [currently: right]

display.column_space No description available.
    [default: 12] [currently: 12]

display.date_dayfirst : boolean
    When True, prints and parses dates with the day first, eg 20/01/2005
    [default: False] [currently: False]

display.date_yearfirst : boolean
    When True, prints and parses dates with the year first, eg 2005/01/20
    [default: False] [currently: False]

display.encoding : str/unicode
    Defaults to the detected encoding of the console.
    Specifies the encoding to be used for strings returned by to_string,
    these are generally strings meant to be displayed on the console.
    [default: UTF-8] [currently: UTF-8]

display.expand_frame_repr : boolean
    Whether to print out the full DataFrame repr for wide DataFrames across
    multiple lines, `max_columns` is still respected, but the output will
    wrap-around across multiple "pages" if its width exceeds `display.width`.
    [default: True] [currently: True]

display.float_format : callable
    The callable should accept a floating point number and return
    a string with the desired format of the number. This is used
    in some places like SeriesFormatter.
    See formats.format.EngFormatter for an example.
    [default: None] [currently: <built-in method format of str object at 0x11411fe68>]

display.height : int
    Deprecated.
    [default: 60] [currently: 60]
    (Deprecated, use `display.max_rows` instead.)

display.large_repr : 'truncate'/'info'
    For DataFrames exceeding max_rows/max_cols, the repr (and HTML repr) can
    show a truncated table (the default from 0.13), or switch to the view from
    df.info() (the behaviour in earlier versions of pandas).
    [default: truncate] [currently: truncate]

display.latex.escape : bool
    This specifies if the to_latex method of a Dataframe uses escapes special
    characters.
    method. Valid values: False,True
    [default: True] [currently: True]

display.latex.longtable :bool
    This specifies if the to_latex method of a Dataframe uses the longtable
    format.
    method. Valid values: False,True
    [default: False] [currently: False]

display.latex.repr : boolean
    Whether to produce a latex DataFrame representation for jupyter
    environments that support it.
    (default: False)
    [default: False] [currently: False]

display.line_width : int
    Deprecated.
    [default: 80] [currently: 80]
    (Deprecated, use `display.width` instead.)

display.max_categories : int
    This sets the maximum number of categories pandas should output when
    printing out a `Categorical` or a Series of dtype "category".
    [default: 8] [currently: 8]

display.max_columns : int
    If max_cols is exceeded, switch to truncate view. Depending on
    `large_repr`, objects are either centrally truncated or printed as
    a summary view. 'None' value means unlimited.

    In case python/IPython is running in a terminal and `large_repr`
    equals 'truncate' this can be set to 0 and pandas will auto-detect
    the width of the terminal and print a truncated object which fits
    the screen width. The IPython notebook, IPython qtconsole, or IDLE
    do not run in a terminal and hence it is not possible to do
    correct auto-detection.
    [default: 20] [currently: 20]

display.max_colwidth : int
    The maximum width in characters of a column in the repr of
    a pandas data structure. When the column overflows, a "..."
    placeholder is embedded in the output.
    [default: 50] [currently: 1000]

display.max_info_columns : int
    max_info_columns is used in DataFrame.info method to decide if
    per column information will be printed.
    [default: 100] [currently: 100]

display.max_info_rows : int or None
    df.info() will usually show null-counts for each column.
    For large frames this can be quite slow. max_info_rows and max_info_cols
    limit this null check only to frames with smaller dimensions than
    specified.
    [default: 1690785] [currently: 1690785]

display.max_rows : int
    If max_rows is exceeded, switch to truncate view. Depending on
    `large_repr`, objects are either centrally truncated or printed as
    a summary view. 'None' value means unlimited.

    In case python/IPython is running in a terminal and `large_repr`
    equals 'truncate' this can be set to 0 and pandas will auto-detect
    the height of the terminal and print a truncated object which fits
    the screen height. The IPython notebook, IPython qtconsole, or
    IDLE do not run in a terminal and hence it is not possible to do
    correct auto-detection.
    [default: 60] [currently: 60]

display.max_seq_items : int or None
    when pretty-printing a long sequence, no more then `max_seq_items`
    will be printed. If items are omitted, they will be denoted by the
    addition of "..." to the resulting string.

    If set to None, the number of items to be printed is unlimited.
    [default: 100] [currently: 100]

display.memory_usage : bool, string or None
    This specifies if the memory usage of a DataFrame should be displayed when
    df.info() is called. Valid values True,False,'deep'
    [default: True] [currently: True]

display.mpl_style : bool
    Setting this to 'default' will modify the rcParams used by matplotlib
    to give plots a more pleasing visual style by default.
    Setting this to None/False restores the values to their initial value.
    [default: None] [currently: None]

display.multi_sparse : boolean
    "sparsify" MultiIndex display (don't display repeated
    elements in outer levels within groups)
    [default: True] [currently: True]

display.notebook_repr_html : boolean
    When True, IPython notebook will use html representation for
    pandas objects (if it is available).
    [default: True] [currently: True]

display.pprint_nest_depth : int
    Controls the number of nested levels to process when pretty-printing
    [default: 3] [currently: 3]

display.precision : int
    Floating point output precision (number of significant digits). This is
    only a suggestion
    [default: 6] [currently: 3]

display.show_dimensions : boolean or 'truncate'
    Whether to print out dimensions at the end of DataFrame repr.
    If 'truncate' is specified, only print out the dimensions if the
    frame is truncated (e.g. not display all rows and/or columns)
    [default: truncate] [currently: truncate]

display.unicode.ambiguous_as_wide : boolean
    Whether to use the Unicode East Asian Width to calculate the display text
    width.
    Enabling this may affect to the performance (default: False)
    [default: False] [currently: False]

display.unicode.east_asian_width : boolean
    Whether to use the Unicode East Asian Width to calculate the display text
    width.
    Enabling this may affect to the performance (default: False)
    [default: False] [currently: False]

display.width : int
    Width of the display in characters. In case python/IPython is running in
    a terminal this can be set to None and pandas will correctly auto-detect
    the width.
    Note that the IPython notebook, IPython qtconsole, or IDLE do not run in a
    terminal and hence it is not possible to correctly detect the width.
    [default: 80] [currently: 80]

io.excel.xls.writer : string
    The default Excel writer engine for 'xls' files. Available options:
    'xlwt' (the default).
    [default: xlwt] [currently: xlwt]

io.excel.xlsm.writer : string
    The default Excel writer engine for 'xlsm' files. Available options:
    'openpyxl' (the default).
    [default: openpyxl] [currently: openpyxl]

io.excel.xlsx.writer : string
    The default Excel writer engine for 'xlsx' files. Available options:
    'xlsxwriter' (the default), 'openpyxl'.
    [default: xlsxwriter] [currently: xlsxwriter]

io.hdf.default_format : format
    default format writing format, if None, then
    put will default to 'fixed' and append will default to 'table'
    [default: None] [currently: None]

io.hdf.dropna_table : boolean
    drop ALL nan rows when appending to a table
    [default: False] [currently: False]

mode.chained_assignment : string
    Raise an exception, warn, or no action if trying to use chained assignment,
    The default is warn
    [default: warn] [currently: warn]

mode.sim_interactive : boolean
    Whether to simulate interactive mode for purposes of testing
    [default: False] [currently: False]

mode.use_inf_as_null : boolean
    True means treat None, NaN, INF, -INF as null (old way),
    False means None and NaN are null, but INF, -INF are not null
    (new way).
    [default: False] [currently: False]

# specific searching
pd.describe_option('rows')

display.max_info_rows : int or None
    df.info() will usually show null-counts for each column.
    For large frames this can be quite slow. max_info_rows and max_info_cols
    limit this null check only to frames with smaller dimensions than
    specified.
    [default: 1690785] [currently: 1690785]

display.max_rows : int
    If max_rows is exceeded, switch to truncate view. Depending on
    `large_repr`, objects are either centrally truncated or printed as
    a summary view. 'None' value means unlimited.

    In case python/IPython is running in a terminal and `large_repr`
    equals 'truncate' this can be set to 0 and pandas will auto-detect
    the height of the terminal and print a truncated object which fits
    the screen height. The IPython notebook, IPython qtconsole, or
    IDLE do not run in a terminal and hence it is not possible to do
    correct auto-detection.
    [default: 60] [currently: 60]

# reset all options
pd.reset_option('all')

# do not worry about the warning

height has been deprecated.

line_width has been deprecated, use display.width instead (currently both are
identical)

/Users/ritchieng/anaconda3/envs/py3k/lib/python3.5/site-packages/ipykernel/__main__.py:2: FutureWarning:
mpl_style had been deprecated and will be removed in a future version.
Use `matplotlib.pyplot.style.use` instead.

  from ipykernel import kernelapp as app

	country	beer_servings	spirit_servings	wine_servings	total_litres_of_pure_alcohol	continent
0	Afghanistan	0	0	0	0.0	Asia
1	Albania	89	132	54	4.9	Europe
2	Algeria	25	0	14	0.7	Africa
3	Andorra	245	138	312	12.4	Europe
4	Angola	217	57	45	5.9	Africa
5	Antigua & Barbuda	102	128	45	4.9	North America
6	Argentina	193	25	221	8.3	South America
7	Armenia	21	179	11	3.8	Europe
8	Australia	261	72	212	10.4	Oceania
9	Austria	279	75	191	9.7	Europe
10	Azerbaijan	21	46	5	1.3	Europe
11	Bahamas	122	176	51	6.3	North America
12	Bahrain	42	63	7	2.0	Asia
13	Bangladesh	0	0	0	0.0	Asia
14	Barbados	143	173	36	6.3	North America
15	Belarus	142	373	42	14.4	Europe
16	Belgium	295	84	212	10.5	Europe
17	Belize	263	114	8	6.8	North America
18	Benin	34	4	13	1.1	Africa
19	Bhutan	23	0	0	0.4	Asia
20	Bolivia	167	41	8	3.8	South America
21	Bosnia-Herzegovina	76	173	8	4.6	Europe
22	Botswana	173	35	35	5.4	Africa
23	Brazil	245	145	16	7.2	South America
24	Brunei	31	2	1	0.6	Asia
25	Bulgaria	231	252	94	10.3	Europe
26	Burkina Faso	25	7	7	4.3	Africa
27	Burundi	88	0	0	6.3	Africa
28	Cote d'Ivoire	37	1	7	4.0	Africa
29	Cabo Verde	144	56	16	4.0	Africa
...	...	...	...	...	...	...
163	Suriname	128	178	7	5.6	South America
164	Swaziland	90	2	2	4.7	Africa
165	Sweden	152	60	186	7.2	Europe
166	Switzerland	185	100	280	10.2	Europe
167	Syria	5	35	16	1.0	Asia
168	Tajikistan	2	15	0	0.3	Asia
169	Thailand	99	258	1	6.4	Asia
170	Macedonia	106	27	86	3.9	Europe
171	Timor-Leste	1	1	4	0.1	Asia
172	Togo	36	2	19	1.3	Africa
173	Tonga	36	21	5	1.1	Oceania
174	Trinidad & Tobago	197	156	7	6.4	North America
175	Tunisia	51	3	20	1.3	Africa
176	Turkey	51	22	7	1.4	Asia
177	Turkmenistan	19	71	32	2.2	Asia
178	Tuvalu	6	41	9	1.0	Oceania
179	Uganda	45	9	0	8.3	Africa
180	Ukraine	206	237	45	8.9	Europe
181	United Arab Emirates	16	135	5	2.8	Asia
182	United Kingdom	219	126	195	10.4	Europe
183	Tanzania	36	6	1	5.7	Africa
184	USA	249	158	84	8.7	North America
185	Uruguay	115	35	220	6.6	South America
186	Uzbekistan	25	101	8	2.4	Asia
187	Vanuatu	21	18	11	0.9	Oceania
188	Venezuela	333	100	3	7.7	South America
189	Vietnam	111	2	1	2.0	Asia
190	Yemen	6	0	0	0.1	Asia
191	Zambia	32	19	4	2.5	Africa
192	Zimbabwe	64	18	4	4.7	Africa

	country	beer_servings	spirit_servings	wine_servings	total_litres_of_pure_alcohol	continent
0	Afghanistan	0	0	0	0.0	Asia
1	Albania	89	132	54	4.9	Europe
2	Algeria	25	0	14	0.7	Africa
3	Andorra	245	138	312	12.4	Europe
4	Angola	217	57	45	5.9	Africa
5	Antigua & Barbuda	102	128	45	4.9	North America
6	Argentina	193	25	221	8.3	South America
7	Armenia	21	179	11	3.8	Europe
8	Australia	261	72	212	10.4	Oceania
9	Austria	279	75	191	9.7	Europe
10	Azerbaijan	21	46	5	1.3	Europe
11	Bahamas	122	176	51	6.3	North America
12	Bahrain	42	63	7	2.0	Asia
13	Bangladesh	0	0	0	0.0	Asia
14	Barbados	143	173	36	6.3	North America
15	Belarus	142	373	42	14.4	Europe
16	Belgium	295	84	212	10.5	Europe
17	Belize	263	114	8	6.8	North America
18	Benin	34	4	13	1.1	Africa
19	Bhutan	23	0	0	0.4	Asia
20	Bolivia	167	41	8	3.8	South America
21	Bosnia-Herzegovina	76	173	8	4.6	Europe
22	Botswana	173	35	35	5.4	Africa
23	Brazil	245	145	16	7.2	South America
24	Brunei	31	2	1	0.6	Asia
25	Bulgaria	231	252	94	10.3	Europe
26	Burkina Faso	25	7	7	4.3	Africa
27	Burundi	88	0	0	6.3	Africa
28	Cote d'Ivoire	37	1	7	4.0	Africa
29	Cabo Verde	144	56	16	4.0	Africa
30	Cambodia	57	65	1	2.2	Asia
31	Cameroon	147	1	4	5.8	Africa
32	Canada	240	122	100	8.2	North America
33	Central African Republic	17	2	1	1.8	Africa
34	Chad	15	1	1	0.4	Africa
35	Chile	130	124	172	7.6	South America
36	China	79	192	8	5.0	Asia
37	Colombia	159	76	3	4.2	South America
38	Comoros	1	3	1	0.1	Africa
39	Congo	76	1	9	1.7	Africa
40	Cook Islands	0	254	74	5.9	Oceania
41	Costa Rica	149	87	11	4.4	North America
42	Croatia	230	87	254	10.2	Europe
43	Cuba	93	137	5	4.2	North America
44	Cyprus	192	154	113	8.2	Europe
45	Czech Republic	361	170	134	11.8	Europe
46	North Korea	0	0	0	0.0	Asia
47	DR Congo	32	3	1	2.3	Africa
48	Denmark	224	81	278	10.4	Europe
49	Djibouti	15	44	3	1.1	Africa
50	Dominica	52	286	26	6.6	North America
51	Dominican Republic	193	147	9	6.2	North America
52	Ecuador	162	74	3	4.2	South America
53	Egypt	6	4	1	0.2	Africa
54	El Salvador	52	69	2	2.2	North America
55	Equatorial Guinea	92	0	233	5.8	Africa
56	Eritrea	18	0	0	0.5	Africa
57	Estonia	224	194	59	9.5	Europe
58	Ethiopia	20	3	0	0.7	Africa
59	Fiji	77	35	1	2.0	Oceania
60	Finland	263	133	97	10.0	Europe
61	France	127	151	370	11.8	Europe
62	Gabon	347	98	59	8.9	Africa
63	Gambia	8	0	1	2.4	Africa
64	Georgia	52	100	149	5.4	Europe
65	Germany	346	117	175	11.3	Europe
66	Ghana	31	3	10	1.8	Africa
67	Greece	133	112	218	8.3	Europe
68	Grenada	199	438	28	11.9	North America
69	Guatemala	53	69	2	2.2	North America
70	Guinea	9	0	2	0.2	Africa
71	Guinea-Bissau	28	31	21	2.5	Africa
72	Guyana	93	302	1	7.1	South America
73	Haiti	1	326	1	5.9	North America
74	Honduras	69	98	2	3.0	North America
75	Hungary	234	215	185	11.3	Europe
76	Iceland	233	61	78	6.6	Europe
77	India	9	114	0	2.2	Asia
78	Indonesia	5	1	0	0.1	Asia
79	Iran	0	0	0	0.0	Asia
80	Iraq	9	3	0	0.2	Asia
81	Ireland	313	118	165	11.4	Europe
82	Israel	63	69	9	2.5	Asia
83	Italy	85	42	237	6.5	Europe
84	Jamaica	82	97	9	3.4	North America
85	Japan	77	202	16	7.0	Asia
86	Jordan	6	21	1	0.5	Asia
87	Kazakhstan	124	246	12	6.8	Asia
88	Kenya	58	22	2	1.8	Africa
89	Kiribati	21	34	1	1.0	Oceania
90	Kuwait	0	0	0	0.0	Asia
91	Kyrgyzstan	31	97	6	2.4	Asia
92	Laos	62	0	123	6.2	Asia
93	Latvia	281	216	62	10.5	Europe
94	Lebanon	20	55	31	1.9	Asia
95	Lesotho	82	29	0	2.8	Africa
96	Liberia	19	152	2	3.1	Africa
97	Libya	0	0	0	0.0	Africa
98	Lithuania	343	244	56	12.9	Europe
99	Luxembourg	236	133	271	11.4	Europe
100	Madagascar	26	15	4	0.8	Africa
101	Malawi	8	11	1	1.5	Africa
102	Malaysia	13	4	0	0.3	Asia
103	Maldives	0	0	0	0.0	Asia
104	Mali	5	1	1	0.6	Africa
105	Malta	149	100	120	6.6	Europe
106	Marshall Islands	0	0	0	0.0	Oceania
107	Mauritania	0	0	0	0.0	Africa
108	Mauritius	98	31	18	2.6	Africa
109	Mexico	238	68	5	5.5	North America
110	Micronesia	62	50	18	2.3	Oceania
111	Monaco	0	0	0	0.0	Europe
112	Mongolia	77	189	8	4.9	Asia
113	Montenegro	31	114	128	4.9	Europe
114	Morocco	12	6	10	0.5	Africa
115	Mozambique	47	18	5	1.3	Africa
116	Myanmar	5	1	0	0.1	Asia
117	Namibia	376	3	1	6.8	Africa
118	Nauru	49	0	8	1.0	Oceania
119	Nepal	5	6	0	0.2	Asia
120	Netherlands	251	88	190	9.4	Europe
121	New Zealand	203	79	175	9.3	Oceania
122	Nicaragua	78	118	1	3.5	North America
123	Niger	3	2	1	0.1	Africa
124	Nigeria	42	5	2	9.1	Africa
125	Niue	188	200	7	7.0	Oceania
126	Norway	169	71	129	6.7	Europe
127	Oman	22	16	1	0.7	Asia
128	Pakistan	0	0	0	0.0	Asia
129	Palau	306	63	23	6.9	Oceania
130	Panama	285	104	18	7.2	North America
131	Papua New Guinea	44	39	1	1.5	Oceania
132	Paraguay	213	117	74	7.3	South America
133	Peru	163	160	21	6.1	South America
134	Philippines	71	186	1	4.6	Asia
135	Poland	343	215	56	10.9	Europe
136	Portugal	194	67	339	11.0	Europe
137	Qatar	1	42	7	0.9	Asia
138	South Korea	140	16	9	9.8	Asia
139	Moldova	109	226	18	6.3	Europe
140	Romania	297	122	167	10.4	Europe
141	Russian Federation	247	326	73	11.5	Asia
142	Rwanda	43	2	0	6.8	Africa
143	St. Kitts & Nevis	194	205	32	7.7	North America
144	St. Lucia	171	315	71	10.1	North America
145	St. Vincent & the Grenadines	120	221	11	6.3	North America
146	Samoa	105	18	24	2.6	Oceania
147	San Marino	0	0	0	0.0	Europe
148	Sao Tome & Principe	56	38	140	4.2	Africa
149	Saudi Arabia	0	5	0	0.1	Asia
150	Senegal	9	1	7	0.3	Africa
151	Serbia	283	131	127	9.6	Europe
152	Seychelles	157	25	51	4.1	Africa
153	Sierra Leone	25	3	2	6.7	Africa
154	Singapore	60	12	11	1.5	Asia
155	Slovakia	196	293	116	11.4	Europe
156	Slovenia	270	51	276	10.6	Europe
157	Solomon Islands	56	11	1	1.2	Oceania
158	Somalia	0	0	0	0.0	Africa
159	South Africa	225	76	81	8.2	Africa
160	Spain	284	157	112	10.0	Europe
161	Sri Lanka	16	104	0	2.2	Asia
162	Sudan	8	13	0	1.7	Africa
163	Suriname	128	178	7	5.6	South America
164	Swaziland	90	2	2	4.7	Africa
165	Sweden	152	60	186	7.2	Europe
166	Switzerland	185	100	280	10.2	Europe
167	Syria	5	35	16	1.0	Asia
168	Tajikistan	2	15	0	0.3	Asia
169	Thailand	99	258	1	6.4	Asia
170	Macedonia	106	27	86	3.9	Europe
171	Timor-Leste	1	1	4	0.1	Asia
172	Togo	36	2	19	1.3	Africa
173	Tonga	36	21	5	1.1	Oceania
174	Trinidad & Tobago	197	156	7	6.4	North America
175	Tunisia	51	3	20	1.3	Africa
176	Turkey	51	22	7	1.4	Asia
177	Turkmenistan	19	71	32	2.2	Asia
178	Tuvalu	6	41	9	1.0	Oceania
179	Uganda	45	9	0	8.3	Africa
180	Ukraine	206	237	45	8.9	Europe
181	United Arab Emirates	16	135	5	2.8	Asia
182	United Kingdom	219	126	195	10.4	Europe
183	Tanzania	36	6	1	5.7	Africa
184	USA	249	158	84	8.7	North America
185	Uruguay	115	35	220	6.6	South America
186	Uzbekistan	25	101	8	2.4	Asia
187	Vanuatu	21	18	11	0.9	Oceania
188	Venezuela	333	100	3	7.7	South America
189	Vietnam	111	2	1	2.0	Asia
190	Yemen	6	0	0	0.1	Asia
191	Zambia	32	19	4	2.5	Africa
192	Zimbabwe	64	18	4	4.7	Africa

	country	beer_servings	spirit_servings	wine_servings	total_litres_of_pure_alcohol	continent
0	Afghanistan	0	0	0	0.0	Asia
1	Albania	89	132	54	4.9	Europe
2	Algeria	25	0	14	0.7	Africa
3	Andorra	245	138	312	12.4	Europe
4	Angola	217	57	45	5.9	Africa
5	Antigua & Barbuda	102	128	45	4.9	North America
6	Argentina	193	25	221	8.3	South America
7	Armenia	21	179	11	3.8	Europe
8	Australia	261	72	212	10.4	Oceania
9	Austria	279	75	191	9.7	Europe
10	Azerbaijan	21	46	5	1.3	Europe
11	Bahamas	122	176	51	6.3	North America
12	Bahrain	42	63	7	2.0	Asia
13	Bangladesh	0	0	0	0.0	Asia
14	Barbados	143	173	36	6.3	North America
15	Belarus	142	373	42	14.4	Europe
16	Belgium	295	84	212	10.5	Europe
17	Belize	263	114	8	6.8	North America
18	Benin	34	4	13	1.1	Africa
19	Bhutan	23	0	0	0.4	Asia
20	Bolivia	167	41	8	3.8	South America
21	Bosnia-Herzegovina	76	173	8	4.6	Europe
22	Botswana	173	35	35	5.4	Africa
23	Brazil	245	145	16	7.2	South America
24	Brunei	31	2	1	0.6	Asia
25	Bulgaria	231	252	94	10.3	Europe
26	Burkina Faso	25	7	7	4.3	Africa
27	Burundi	88	0	0	6.3	Africa
28	Cote d'Ivoire	37	1	7	4.0	Africa
29	Cabo Verde	144	56	16	4.0	Africa
...	...	...	...	...	...	...
163	Suriname	128	178	7	5.6	South America
164	Swaziland	90	2	2	4.7	Africa
165	Sweden	152	60	186	7.2	Europe
166	Switzerland	185	100	280	10.2	Europe
167	Syria	5	35	16	1.0	Asia
168	Tajikistan	2	15	0	0.3	Asia
169	Thailand	99	258	1	6.4	Asia
170	Macedonia	106	27	86	3.9	Europe
171	Timor-Leste	1	1	4	0.1	Asia
172	Togo	36	2	19	1.3	Africa
173	Tonga	36	21	5	1.1	Oceania
174	Trinidad & Tobago	197	156	7	6.4	North America
175	Tunisia	51	3	20	1.3	Africa
176	Turkey	51	22	7	1.4	Asia
177	Turkmenistan	19	71	32	2.2	Asia
178	Tuvalu	6	41	9	1.0	Oceania
179	Uganda	45	9	0	8.3	Africa
180	Ukraine	206	237	45	8.9	Europe
181	United Arab Emirates	16	135	5	2.8	Asia
182	United Kingdom	219	126	195	10.4	Europe
183	Tanzania	36	6	1	5.7	Africa
184	USA	249	158	84	8.7	North America
185	Uruguay	115	35	220	6.6	South America
186	Uzbekistan	25	101	8	2.4	Asia
187	Vanuatu	21	18	11	0.9	Oceania
188	Venezuela	333	100	3	7.7	South America
189	Vietnam	111	2	1	2.0	Asia
190	Yemen	6	0	0	0.1	Asia
191	Zambia	32	19	4	2.5	Africa
192	Zimbabwe	64	18	4	4.7	Africa

	PassengerId	Survived	Pclass	Name	Sex	Age	SibSp	Ticket	Fare	Cabin	Embarked
0	1	0	3	Braund, Mr. Owen Harris	male	22.0	1	A/5 21171	7.250	NaN	S
1	2	1	1	Cumings, Mrs. John Bradley (Florence Briggs Thayer)	female	38.0	1	PC 17599	71.283	C85	C
2	3	1	3	Heikkinen, Miss. Laina	female	26.0	0	STON/O2. 3101282	7.925	NaN	S
3	4	1	1	Futrelle, Mrs. Jacques Heath (Lily May Peel)	female	35.0	1	113803	53.100	C123	S
4	5	0	3	Allen, Mr. William Henry	male	35.0	0	373450	8.050	NaN	S

	PassengerId	Survived	Pclass	Name	Sex	Age	SibSp	Ticket	Fare	Cabin	Embarked
0	1	0	3	Braund, Mr. Owen Harris	male	22.0	1	A/5 21171	7.250	NaN	S
1	2	1	1	Cumings, Mrs. John Bradley (Florence Briggs Thayer)	female	38.0	1	PC 17599	71.283	C85	C
2	3	1	3	Heikkinen, Miss. Laina	female	26.0	0	STON/O2. 3101282	7.925	NaN	S
3	4	1	1	Futrelle, Mrs. Jacques Heath (Lily May Peel)	female	35.0	1	113803	53.100	C123	S
4	5	0	3	Allen, Mr. William Henry	male	35.0	0	373450	8.050	NaN	S

Changing Display Options

Changing display options in pandas¶