The Big Data Landscape Diagram 2016 – Version


Having started my journey in Data Science. I came across Mean Squared Error several times and realised how important that concept is. Then I started working on project and needed to really understand what Mean Squared Error is ? So what is Mean Squared Error ? Simply, let’s say you are building your model. And…
GDPR stands for General Data Protection Regulation (GDPR) also referred to as the EU General Data Protection Regulation (GDPR). According to the EUGDPR website , The EU General Data Protection Regulation (GDPR) is the most important change in data privacy regulation in 20 years. The EU General Data Protection Regulation (GDPR) replaces the Data Protection Directive 95/46/EC and was designed to harmonize…
Adding actions to messages boxes Message Boxes, like most functions, return one of these values and their respective meanings Button Pressed Return Values: OK = $IDOK (1) CANCEL = $IDCANCEL (2) ABORT = $IDABORT (3) RETRY = $IDRETRY (4) IGNORE = $IDIGNORE (5) YES = $IDYES (6) NO = $IDNO (7) CONTINUE ** = $IDCONTINUE (11) TRY…
Summarizing Data This week we are looking at five most common aggregate functions used to summarize information stored in tables: COUNT and SUM very frequently. COUNT is the only aggregate function that can work on any type of variable. The other four aggregate functions are only appropriate for numerical data. All aggregate functions require you…
In this quick notes, we will have a look at Rank and Sort in Series and DataFrames in Python In [1]:
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import numpy as np import pandas as pd from pandas import Series, DataFrame |
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#make a series ser1 = Series(range(3), index=['C','A','B']) ser1 |
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C 0 A 1 B 2 dtype: int32 |
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#sort index of series ser1.sort_index() |
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A 1 B 2 C 0 dtype: int32 |
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#order or sort by values ser1.order() |
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C:\Users\adaba\Anaconda3\lib\site-packages\ipykernel\__main__.py:2: FutureWarning: order is deprecated, use sort_values(...) from ipykernel import kernelapp as app |
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C 0 A 1 B 2 dtype: int32 |
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ser1.sort_values() |
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C 0 A 1 B 2 dtype: int32 |
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from numpy.random import randn |
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#make a series by passing in 10 random numbers ser2 = Series(randn(10)) ser2 |
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0 -0.201751 1 1.534109 2 0.542825 3 1.421174 4 -0.173771 5 0.002573 6 -0.490208 7 -0.765340 8 -2.546040 9 -0.456699 dtype: float64 |
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#sort the values ser2.sort_values() |
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