Pandasimport pandas as pd | pd.series([values])
ad = {}
area = pd.series(ad) | Retrieving Values | area["a"]
To see all keys:
area.keys()
data.items() | Dataframe as dictionary | area = pd.series({...})
data = pd.Dataframe({"area":area,}) | Opening data | import pandas as pd
import numpy as np
dat = np.genfromtxt('phoneBook.csv',delimiter =',',skip_header=1,dtype='<U16') | Grouping | index = pd.MultiIndex.from_tuples(index)
index
pop = pop.reindex(index) pop
pop[:, 2010] |
| | Merging and JoiningMerging | pd.merge() | | | df = pd.merge() | Many to one | Duplicate entries
display('df3', 'df4', 'pd.merge(df3, df4)') | Merge Key | Add on = "key column name" | Drop | .drop('name', axis=1) |
Aggregation and GroupingAggregation Functions | count() | Total number of items
first(), last() | First and last item
mean(), median() | Mean and median
min(), max() | Minimum and maximum
std(), var() | Standard deviation and variance
mad() | Mean absolute deviation
prod() | Product of all items
sum() | Sum of all items | Grouping | name.groupy("key") |
| | Pivot TablesPivot Tables by Hand | Require groupby | Pivot | name.pivot_table("what is taking the action", index = "groupby row" , columns = "groupbycol") | Aggregation Functions | name.pivot_table( index = "groupby row" , columns = "groupbycol" , aggfunc={'taking action':sum, 'taking action':'mean'}) |
| | MatplotlibLine Plots | Set linspace
x = np.linspace(0, 10, 100) | Creating figure and axis | fig = plt.figure()
ax = plt.axes() | Add graph and x,y | x = np.linspace(0, 10, 1000)
y = np.sin(x)
plt.plot(x,y)
plt.show()
| Changing linestyle and color | plt.plot(x,y,linestyle='--', color='c') | Multile curves and a legend | plt.plot(x,np.sin(x-.5),color='g',label="sin(x-0.5)")
plt.plot(x,np.sin(x-1),color='pink', label = "sin(x-1)")
plt.plot(x,np.cos(x-0.5),color='c',linestyle='--',label = "cos(x-0.5)") plt.legend() plt.show() | Adding limits | plt.xlim(-5,12)
plt.ylim(-2,2) | Scatter Plot | x = np.random.randint(-1000,1000,150)
y = np.random.randint(-1000,1000,150) plt.scatter(x,y)
or plt.plot(x,y,'o'); | Other ways for plt | plt.xlabel() → ax.set_xlabel()
plt.ylabel() → ax.set_ylabel()
lt.xlim() → ax.set_xlim()
plt.ylim() → ax.set_ylim()
plt.title() → ax.set_title() | Histograms | fig = plt.figure()
ax = plt.axes()
ax.hist(data); |
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