In [1]:
2 + 2
Out[1]:
4
In [8]:
myvar = "this is a string"
In [10]:
print(myvar)

this is not a string
In [9]:
myvar = "this is not a string"
In [12]:
myvar2 = 8
In [13]:
print(myvar2)

8
In [15]:
print("this is not a string")

this is not a string
In [16]:
print(myvar)

this is not a string
In [18]:
print(this is not a string)

  File "<ipython-input-18-fa8ece6e3fbd>", line 1
    print(this is not a string)
                             ^
SyntaxError: invalid syntax
In [23]:
temp_C = 50
temp_C * 9 / 5 + 32
temp_C + 20
# Prints only last line result
Out[23]:
70
In [25]:
temp_C = 50
temp_F = temp_C * 9 / 5 + 32
In [27]:
print(temp_F)  # Print a value that we previously assigned

122.0
In [30]:
# Checkpoint 1

x = 1
y = 2

# Swap the values of x and y (hint: use a third variable)

#x, y = y, x
z = x
a = y
x = a
y = z

print(x)
print(y)

2
1
In [31]:
chemist = "Linus Pauling"
In [32]:
print(chemist)

Linus Pauling
In [33]:
chemist[0:5]
Out[33]:
'Linus'
In [35]:
chemist[0]
Out[35]:
'L'
In [36]:
chemist[1]
Out[36]:
'i'
In [38]:
first_value = "initial"
second_value = first_value[1:5]
first_value = second_value[2]
print(first_value)

t
In [39]:
physicist = "Max Planck"
len(physicist)
Out[39]:
10
In [41]:
length = len(physicist)
physicist[length - 1]
Out[41]:
'k'
In [43]:
physicist[2:length]
Out[43]:
'x Planck'
In [44]:
physicist[2:]
Out[44]:
'x Planck'
In [45]:
physicist[:3]
Out[45]:
'Max'
In [46]:
type(temp_C)
Out[46]:
int
In [47]:
type(physicist)
Out[47]:
str
In [48]:
chemist + physicist
Out[48]:
'Linus PaulingMax Planck'
In [49]:
chemist + temp_C

------------------------------------------------------------
TypeError                  Traceback (most recent call last)
<ipython-input-49-dd27f9da2696> in <module>()
----> 1 chemist + temp_C

TypeError: must be str, not int
In [52]:
8 / 3
Out[52]:
2.6666666666666665
In [51]:
type(8 / 3)
Out[51]:
float
In [53]:
temp_C + (8 / 3)
Out[53]:
52.666666666666664
In [56]:
type(temp_F)
Out[56]:
float
In [57]:
"(" + str(temp_F) + ")"
Out[57]:
'(122.0)'
In [58]:
type(10)
Out[58]:
int
In [59]:
float(10)
Out[59]:
10.0
In [60]:
int(10.999)
Out[60]:
10
In [ ]:
# print, len, type, str, int, float
In [61]:
print()



















In [62]:



    


print




















Out[62]:








<function print>



















In [63]:



    


max(1, 5, 3)




















Out[63]:








5



















In [64]:



    


help(max)


























Help on built-in function max in module builtins:

max(...)
    max(iterable, *[, default=obj, key=func]) -> value
    max(arg1, arg2, *args, *[, key=func]) -> value
    
    With a single iterable argument, return its biggest item. The
    default keyword-only argument specifies an object to return if
    the provided iterable is empty.
    With two or more arguments, return the largest argument.




















In [66]:



    


planck_length = len(physicist)

















In [67]:



    


output = print("a string")


























a string



















In [68]:



    


print(output)


























None



















In [69]:



    


type(output)




















Out[69]:








NoneType



















In [70]:



    


mean(1, 4, 5)


























------------------------------------------------------------
NameError                  Traceback (most recent call last)
<ipython-input-70-f7159d372e47> in <module>()
----> 1 mean(1, 4, 5)

NameError: name 'mean' is not defined


















In [73]:



    


import math

















In [74]:



    


dir(math)




















Out[74]:








['__doc__',
 '__file__',
 '__loader__',
 '__name__',
 '__package__',
 '__spec__',
 'acos',
 'acosh',
 'asin',
 'asinh',
 'atan',
 'atan2',
 'atanh',
 'ceil',
 'copysign',
 'cos',
 'cosh',
 'degrees',
 'e',
 'erf',
 'erfc',
 'exp',
 'expm1',
 'fabs',
 'factorial',
 'floor',
 'fmod',
 'frexp',
 'fsum',
 'gamma',
 'gcd',
 'hypot',
 'inf',
 'isclose',
 'isfinite',
 'isinf',
 'isnan',
 'ldexp',
 'lgamma',
 'log',
 'log10',
 'log1p',
 'log2',
 'modf',
 'nan',
 'pi',
 'pow',
 'radians',
 'sin',
 'sinh',
 'sqrt',
 'tan',
 'tanh',
 'tau',
 'trunc']



















In [76]:



    


import stat

















In [77]:



    


htam = math

















In [78]:



    


# Checkpoint

radiance = 1.0
radiance = max(2.1, 2.0 + min(radiance, radiance - 0.5))

# What is the order of operations?
# What is the final value of radiance?
print(radiance)


























2.5



















In [82]:



    


import pandas

















In [84]:



    


europe = pandas.read_csv("gapminder_gdp_europe.csv")

















In [85]:



    


europe.mean()




















Out[85]:








gdpPercap_1952     5661.057435
gdpPercap_1957     6963.012816
gdpPercap_1962     8365.486814
gdpPercap_1967    10143.823757
gdpPercap_1972    12479.575246
gdpPercap_1977    14283.979110
gdpPercap_1982    15617.896551
gdpPercap_1987    17214.310727
gdpPercap_1992    17061.568084
gdpPercap_1997    19076.781802
gdpPercap_2002    21711.732422
gdpPercap_2007    25054.481636
dtype: float64



















In [86]:



    


europe.std()




















Out[86]:








gdpPercap_1952     3114.060493
gdpPercap_1957     3677.950146
gdpPercap_1962     4199.193906
gdpPercap_1967     4724.983889
gdpPercap_1972     5509.691411
gdpPercap_1977     5874.464896
gdpPercap_1982     6453.234827
gdpPercap_1987     7482.957960
gdpPercap_1992     9109.804361
gdpPercap_1997    10065.457716
gdpPercap_2002    11197.355517
gdpPercap_2007    11800.339811
dtype: float64



















In [ ]:



    


pandas.read_csv

















In [88]:



    


europe = pandas.read_csv("gapminder_gdp_europe.csv",
                         index_col="country")
europe.head()




















Out[88]:











  
    

      
      gdpPercap_1952
      gdpPercap_1957
      gdpPercap_1962
      gdpPercap_1967
      gdpPercap_1972
      gdpPercap_1977
      gdpPercap_1982
      gdpPercap_1987
      gdpPercap_1992
      gdpPercap_1997
      gdpPercap_2002
      gdpPercap_2007
    

    

      country
      
      
      
      
      
      
      
      
      
      
      
      
    

  
  
    

      Albania
      1601.056136
      1942.284244
      2312.888958
      2760.196931
      3313.422188
      3533.003910
      3630.880722
      3738.932735
      2497.437901
      3193.054604
      4604.211737
      5937.029526
    

    

      Austria
      6137.076492
      8842.598030
      10750.721110
      12834.602400
      16661.625600
      19749.422300
      21597.083620
      23687.826070
      27042.018680
      29095.920660
      32417.607690
      36126.492700
    

    

      Belgium
      8343.105127
      9714.960623
      10991.206760
      13149.041190
      16672.143560
      19117.974480
      20979.845890
      22525.563080
      25575.570690
      27561.196630
      30485.883750
      33692.605080
    

    

      Bosnia and Herzegovina
      973.533195
      1353.989176
      1709.683679
      2172.352423
      2860.169750
      3528.481305
      4126.613157
      4314.114757
      2546.781445
      4766.355904
      6018.975239
      7446.298803
    

    

      Bulgaria
      2444.286648
      3008.670727
      4254.337839
      5577.002800
      6597.494398
      7612.240438
      8224.191647
      8239.854824
      6302.623438
      5970.388760
      7696.777725
      10680.792820
    

  






















In [90]:



    


europe.gdpPercap_1952.Austria




















Out[90]:








6137.0764920000001



















In [94]:



    


Austria


























------------------------------------------------------------
NameError                  Traceback (most recent call last)
<ipython-input-94-9da0dddce247> in <module>()
----> 1 Austria

NameError: name 'Austria' is not defined


















In [96]:



    


europe.loc['Austria']




















Out[96]:








gdpPercap_1952     6137.076492
gdpPercap_1957     8842.598030
gdpPercap_1962    10750.721110
gdpPercap_1967    12834.602400
gdpPercap_1972    16661.625600
gdpPercap_1977    19749.422300
gdpPercap_1982    21597.083620
gdpPercap_1987    23687.826070
gdpPercap_1992    27042.018680
gdpPercap_1997    29095.920660
gdpPercap_2002    32417.607690
gdpPercap_2007    36126.492700
Name: Austria, dtype: float64



















In [97]:



    


europe.loc['Austria'].mean()




















Out[97]:








20411.916279333334



















In [98]:



    


europe.columns




















Out[98]:








Index(['gdpPercap_1952', 'gdpPercap_1957', 'gdpPercap_1962', 'gdpPercap_1967',
       'gdpPercap_1972', 'gdpPercap_1977', 'gdpPercap_1982', 'gdpPercap_1987',
       'gdpPercap_1992', 'gdpPercap_1997', 'gdpPercap_2002', 'gdpPercap_2007'],
      dtype='object')



















In [99]:



    


europe.gdpPercap_1952 + europe.gdpPercap_1957




















Out[99]:








country
Albania                    3543.340380
Austria                   14979.674522
Belgium                   18058.065750
Bosnia and Herzegovina     2327.522371
Bulgaria                   5452.957375
Croatia                    7457.468137
Czech Republic            15132.484168
Denmark                   20792.044595
Finland                   13969.934457
France                    15692.644225
Germany                   17331.941043
Greece                     8446.989956
Hungary                   11303.853827
Iceland                   16511.689840
Ireland                   10809.358200
Italy                     11180.060387
Montenegro                 6329.845504
Netherlands               20217.765298
Norway                    21749.394760
Poland                     8763.582718
Portugal                   6842.891610
Romania                    7087.983411
Serbia                     8562.550339
Slovak Republic           11167.922084
Slovenia                  10077.318370
Spain                      8398.837152
Sweden                    18439.722888
Switzerland               32643.722480
Turkey                     4187.855237
United Kingdom            21262.686437
dtype: float64



















In [100]:



    


gdp_1952_and_1957 = europe['gdpPercap_1952'] + europe['gdpPercap_1957']

















In [102]:



    


gdp_1952_and_1957.mean()




















Out[102]:








12624.070250693332



















In [105]:



    


import matplotlib.pyplot

















In [107]:



    


%matplotlib inline

















In [108]:



    


matplotlib.pyplot.hist(europe.gdpPercap_1952)




















Out[108]:








(array([ 3.,  7.,  5.,  4.,  4.,  3.,  3.,  0.,  0.,  1.]),
 array([   973.5331948 ,   2349.60315032,   3725.67310584,   5101.74306136,
          6477.81301688,   7853.8829724 ,   9229.95292792,  10606.02288344,
         11982.09283896,  13358.16279448,  14734.23275   ]),
 <a list of 10 Patch objects>)





































In [110]:



    


matplotlib.pyplot.hist(europe.gdpPercap_1952, bins=20)




















Out[110]:








(array([ 2.,  1.,  2.,  5.,  3.,  2.,  2.,  2.,  3.,  1.,  2.,  1.,  1.,
         2.,  0.,  0.,  0.,  0.,  0.,  1.]),
 array([   973.5331948 ,   1661.56817256,   2349.60315032,   3037.63812808,
          3725.67310584,   4413.7080836 ,   5101.74306136,   5789.77803912,
          6477.81301688,   7165.84799464,   7853.8829724 ,   8541.91795016,
          9229.95292792,   9917.98790568,  10606.02288344,  11294.0578612 ,
         11982.09283896,  12670.12781672,  13358.16279448,  14046.19777224,
         14734.23275   ]),
 <a list of 20 Patch objects>)





































In [111]:



    


europe.loc['Switzerland']




















Out[111]:








gdpPercap_1952    14734.23275
gdpPercap_1957    17909.48973
gdpPercap_1962    20431.09270
gdpPercap_1967    22966.14432
gdpPercap_1972    27195.11304
gdpPercap_1977    26982.29052
gdpPercap_1982    28397.71512
gdpPercap_1987    30281.70459
gdpPercap_1992    31871.53030
gdpPercap_1997    32135.32301
gdpPercap_2002    34480.95771
gdpPercap_2007    37506.41907
Name: Switzerland, dtype: float64



















In [112]:



    


import matplotlib.pyplot as plt

















In [119]:



    


plt.hist(europe.gdpPercap_1952, bins=20, alpha=0.5, label='1952')
plt.hist(europe.gdpPercap_1957, bins=20, alpha=0.5, label='1957')
plt.xlabel('GDP Per-capita (US$2007)')
plt.ylabel('Count')
plt.legend()
plt.title("Economic shifts in post-war Europe")
print()






























































In [120]:



    


europe.loc['Switzerland']




















Out[120]:








gdpPercap_1952    14734.23275
gdpPercap_1957    17909.48973
gdpPercap_1962    20431.09270
gdpPercap_1967    22966.14432
gdpPercap_1972    27195.11304
gdpPercap_1977    26982.29052
gdpPercap_1982    28397.71512
gdpPercap_1987    30281.70459
gdpPercap_1992    31871.53030
gdpPercap_1997    32135.32301
gdpPercap_2002    34480.95771
gdpPercap_2007    37506.41907
Name: Switzerland, dtype: float64



















In [126]:



    


#years = [1952, 1957, 1962, 1967,
#         1972, 1977, 1982, 1987,
#         1992, 1997, 2002, 2007]

years = [int(year) for year in europe.columns.str[-4:]]

















In [128]:



    


plt.scatter(years, europe.loc['Switzerland'])




















Out[128]:








<matplotlib.collections.PathCollection at 0x10c2d9a20>





































In [133]:



    


plt.plot(years, europe.T, label='Switzerland')
#plt.plot(years, europe.loc['France'], label='France')
print()