Ejemplos de DataReader.describe en Python

Ejemplo n.º 1

end = datetime.now()
start = datetime(end.year-1,end.month,end.day)


# In[5]:

# Importing Amazon Stock Prices

AMZN = DataReader('AMZN','yahoo',start,end)


# In[6]:

# Some Basic info about the Amazon Stock

AMZN.describe()


# In[7]:

# Plotting Adjusted Closing price for Amazon Stock

AMZN['Adj Close'].plot(legend=True,figsize=(10,4))


# In[8]:

# Plotting the total volume of stock being traded each day

AMZN['Volume'].plot(legend=True,figsize=(10,4))

Ejemplo n.º 2

Archivo: Stock Market Risk Analysis for Apple.py Proyecto: chandrab/iPythonNotebooks

# Setting the Start and End date for Stock Market Analysis

end = datetime.now()
start = datetime(end.year - 1, end.month, end.day)

# In[5]:

# Importing Apple Stock Prices

AAPL = DataReader('AAPL', 'yahoo', start, end)

# In[6]:

# Some Basic info about the Apple Stock

AAPL.describe()

# In[7]:

# Plotting Adjusted Closing price for Apple Stock

AAPL['Adj Close'].plot(legend=True, figsize=(10, 4))

# In[8]:

# Plotting the total volume of stock being traded each day

AAPL['Volume'].plot(legend=True, figsize=(10, 4))

# In[9]:

Ejemplo n.º 3

Archivo: Stock Market Risk Analysis for Google.py Proyecto: nmp200/Data-Analytics-Projects

# Setting the Start and End date for Stock Market Analysis

end = datetime.now()
start = datetime(end.year - 1, end.month, end.day)

# In[7]:

# Importing Google Stock Prices

GOOG = DataReader('GOOG', 'yahoo', start, end)

# In[8]:

# Some Basic info about the Google Stock

GOOG.describe()

# In[9]:

# Plotting Adjusted Closing price for Google Stock

GOOG['Adj Close'].plot(legend=True, figsize=(10, 4))

# In[10]:

# Total volume of stock being traded each day

GOOG['Volume'].plot(legend=True, figsize=(10, 4))

# In[11]:

Ejemplo n.º 4

Archivo: series_performance.py Proyecto: oolsson/oo_eclipse

from pandas.io.data import DataReader
from datetime import datetime
import pandas as pd
import numpy as np



df = DataReader("GOOG",  "yahoo", datetime(2009,1,1), datetime(2013,5,5))
df=df['Open']
df=df.groupby(df.index.map(lambda x: x.year)).mean()


print df.describe()
print df.to_string

Ejemplo n.º 5

Archivo: Stock Market Risk Analysis for Apple.py Proyecto: namman2/Data-Analytics-Projects

end = datetime.now()
start = datetime(end.year-1,end.month,end.day)


# In[5]:

# Importing Apple Stock Prices

AAPL = DataReader('AAPL','yahoo',start,end)


# In[6]:

# Some Basic info about the Apple Stock

AAPL.describe()


# In[7]:

# Plotting Adjusted Closing price for Apple Stock

AAPL['Adj Close'].plot(legend=True,figsize=(10,4))


# In[8]:

# Plotting the total volume of stock being traded each day

AAPL['Volume'].plot(legend=True,figsize=(10,4))

Ejemplo n.º 6

Archivo: Stock Market Risk Analysis for Google.py Proyecto: namman2/Data-Analytics-Projects

end = datetime.now()
start = datetime(end.year-1,end.month,end.day)


# In[7]:

# Importing Google Stock Prices

GOOG = DataReader('GOOG','yahoo',start,end)


# In[8]:

# Some Basic info about the Google Stock

GOOG.describe()


# In[9]:

# Plotting Adjusted Closing price for Google Stock

GOOG['Adj Close'].plot(legend=True,figsize=(10,4))


# In[10]:

# Total volume of stock being traded each day

GOOG['Volume'].plot(legend=True,figsize=(10,4))

Ejemplo n.º 7

Archivo: Stock Market Risk Analysis for Tesla Motors.py Proyecto: nmp200/Data-Analytics-Projects

# Setting the Start and End date for Stock Market Analysis

end = datetime.now()
start = datetime(end.year - 1, end.month, end.day)

# In[6]:

# Importing Tesla Motors Stock Prices

TSLA = DataReader('TSLA', 'yahoo', start, end)

# In[7]:

# Some Basic info about the Tesla motors Stock

TSLA.describe()

# In[8]:

# Plotting Adjusted Closing price for Tesla Motors Stock

TSLA['Adj Close'].plot(legend=True, figsize=(10, 4))

# In[9]:

# Plotting the total volume of stock being traded each day

TSLA['Volume'].plot(legend=True, figsize=(10, 4))

# In[10]:

Ejemplo n.º 8

Archivo: Stock Market Risk Analysis for ExxonMobil.py Proyecto: nmp200/Data-Analytics-Projects

# Setting the Start and End date for Stock Market Analysis

end = datetime.now()
start = datetime(end.year - 1, end.month, end.day)

# In[6]:

# Importing ExxonMobil Stock Prices

XOM = DataReader('XOM', 'yahoo', start, end)

# In[7]:

# Some Basic info about the ExxonMobil Stock

XOM.describe()

# In[8]:

# Plotting Adjusted Closing price for ExxonMobil Stock

XOM['Adj Close'].plot(legend=True, figsize=(10, 4))

# In[9]:

# Plotting the total volume of stock being traded each day

XOM['Volume'].plot(legend=True, figsize=(10, 4))

# In[10]:

Ejemplo n.º 9

end = datetime.now()
start = datetime(end.year-1,end.month,end.day)


# In[5]:

# Importing Microsoft Stock Prices

MSFT = DataReader('MSFT','yahoo',start,end)


# In[6]:

# Some Basic info about the Microsoft Stock

MSFT.describe()


# In[7]:

# Plotting Adjusted Closing price for Microsoft Stock

MSFT['Adj Close'].plot(legend=True,figsize=(10,4))


# In[8]:

# Plotting the total volume of stock being traded each day

MSFT['Volume'].plot(legend=True,figsize=(10,4))

Ejemplo n.º 10

Archivo: Stock Market Risk Analysis for Tesla Motors.py Proyecto: namman2/Data-Analytics-Projects

end = datetime.now()
start = datetime(end.year-1,end.month,end.day)


# In[6]:

# Importing Tesla Motors Stock Prices

TSLA = DataReader('TSLA','yahoo',start,end)


# In[7]:

# Some Basic info about the Tesla motors Stock

TSLA.describe()


# In[8]:

# Plotting Adjusted Closing price for Tesla Motors Stock

TSLA['Adj Close'].plot(legend=True,figsize=(10,4))


# In[9]:

# Plotting the total volume of stock being traded each day

TSLA['Volume'].plot(legend=True,figsize=(10,4))