How to plot a different candlestick graph on the same figure? - python-3.x
I want to plot candlestick graphs and save each graph I plot. For speed, I want to do this on the same figure.
So far, I can save the first image but the rest are blank.
I've tried using:
pltclf()
plt.cla()
fig.clear()
My code:
import pandas as pd
import matplotlib.pyplot as plt
from mpl_finance import candlestick2_ohlc
from itertools import count
colNames = ['Date', 'Time', 'Open', 'High', 'Low', 'Close']
allData = pd.read_csv('file.csv', header=0, names=colNames, usecols=colNames,
parse_dates={'Datetime': ['Date', 'Time']},
infer_datetime_format=True)
fig, ax = plt.subplots()
for n in count(0, 10):
subset = allData[n:n+10]
plt.axis('off')
try:
candlestick2_ohlc(ax, subset['Open'], subset['High'], subset['Low'],
subset['Close'], width=0.6, colorup='g',
colordown='r', alpha=1)
except ValueError:
print("Graphing done.")
break
fig.savefig("{}.png".format(str(n)))
plt.show()
fig.clf()
CSV File used (file.csv):
Date,Time,OpenBid,HighBid,LowBid,CloseBid
01/02/2009,09:31:00,1212.23,1212.29,1211.77,1211.77
01/02/2009,09:32:00,1211.53,1212.18,1211.29,1211.29
01/02/2009,09:33:00,1209.11,1209.91,1209.11,1209.91
01/02/2009,09:34:00,1210.3,1211.29,1210.3,1211.28
01/02/2009,09:35:00,1213.51,1214.51,1213.11,1213.11
01/02/2009,09:36:00,1212.79,1212.79,1212.56,1212.71
01/02/2009,09:37:00,1213.65,1214.33,1213.65,1213.75
01/02/2009,09:38:00,1213.39,1213.76,1213.39,1213.76
01/02/2009,09:39:00,1211.32,1213.17,1211.32,1213.17
01/02/2009,09:40:00,1213.92,1215.87,1213.92,1215.87
01/02/2009,09:41:00,1215.61,1216.1,1215.4,1216.1
01/02/2009,09:42:00,1215.74,1215.75,1214.07,1214.07
01/02/2009,09:43:00,1214.36,1214.88,1213.87,1214.88
01/02/2009,09:44:00,1215,1215,1213.35,1214.03
01/02/2009,09:45:00,1214.04,1214.44,1214.04,1214.12
01/02/2009,09:46:00,1214.16,1214.56,1214.16,1214.56
01/02/2009,09:47:00,1214.68,1214.93,1214.62,1214.68
01/02/2009,09:48:00,1215.59,1216.11,1215.59,1216.11
01/02/2009,09:49:00,1216.37,1216.37,1215.54,1215.61
01/02/2009,09:50:00,1215.29,1215.29,1214.28,1214.28
01/02/2009,09:51:00,1213.82,1213.82,1212.87,1212.99
01/02/2009,09:52:00,1212.25,1212.44,1212.21,1212.25
01/02/2009,09:53:00,1212.05,1212.05,1210.24,1210.24
01/02/2009,09:54:00,1210.05,1210.21,1209.27,1210.21
01/02/2009,09:55:00,1209.83,1210.68,1209.83,1209.99
01/02/2009,09:56:00,1209.97,1210.91,1209.97,1210.91
01/02/2009,09:57:00,1211.45,1212.62,1211.38,1212.17
01/02/2009,09:58:00,1212.42,1212.42,1212.26,1212.41
01/02/2009,09:59:00,1212.39,1212.39,1212.33,1212.33
01/02/2009,10:00:00,1212.28,1212.28,1211.26,1212.14
01/02/2009,10:01:00,1212.99,1214.66,1212.99,1214.19
01/02/2009,10:02:00,1213.91,1213.91,1213.16,1213.55
01/02/2009,10:03:00,1213.53,1213.53,1213.41,1213.46
01/02/2009,10:04:00,1212.67,1213.21,1212.54,1213.21
01/02/2009,10:05:00,1213.52,1213.81,1213.52,1213.52
01/02/2009,10:06:00,1213.34,1213.4,1213.29,1213.29
01/02/2009,10:07:00,1213.46,1213.6,1213.14,1213.14
01/02/2009,10:08:00,1213.37,1213.81,1213.37,1213.8
01/02/2009,10:09:00,1213.57,1214.5,1213.57,1214.45
01/02/2009,10:10:00,1214.93,1215.03,1214.62,1214.62
I think the issue is to do with candlestick2_ohlc and that it plots to 'ax', but I don't know how to resolve my issue.
Here is what I would do:
from mpl_finance import candlestick2_ohlc
from itertools import count
colNames = ['Date', 'Time', 'Open', 'High', 'Low', 'Close']
allData = pd.read_csv(StringIO(d), header=0, names=colNames, usecols=colNames,
parse_dates={'Datetime': ['Date', 'Time']},
infer_datetime_format=True)
fig, ax = plt.subplots()
for n in count(0, 10):
subset = allData[n:n+10]
plt.axis('off')
if len(subset)>0:
candlestick2_ohlc(ax, subset['Open'], subset['High'], subset['Low'],
subset['Close'], width=0.6, colorup='g',
colordown='r', alpha=1)
fig.savefig("{}.png".format(str(n)))
ax.clear()
else:
break
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Thank you for your help.
Pandas and Matplotlib: Adding tooltip to make interactive
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import pandas as pd
import pandas as pd
from numpy import nan
from matplotlib import dates as mpl_dates
df = dataset
df["Date"] = pd.to_datetime(df["Date"]).dt.strftime('%m/%d/%Y')
#df["Date"] = pd.to_datetime(df["Date"]).apply(lambda x: x.strftime('%B-%Y'))
df.loc[df['Actuals'] == 0, ['Actuals']] = nan
df.loc[df['Actuals'] > 0, ['Predicted_Lower']] = nan
df.loc[df['Actuals'] > 0, ['Predicted_Upper']] = nan
# gca stands for 'get current axis'
ax = plt.gca()
y1 = df['Predicted_Lower']
y2 = df['Predicted_Upper']
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plt.xticks(locs[::3], labels[::3], rotation=45)
plt.show()
plt.xticks(rotation=45)
plt.legend(['Predicted','Actuals'])
plt.xlabel('Date')
df.head(30)
plt.show()
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I'm trying to plot data in two dataframes in two subplots. I'm referring to this link
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import numpy as np
from pprint import pprint
from matplotlib import pyplot as plt
df1 = pd.DataFrame(np.random.randn(10, 10))
df2 = pd.DataFrame(np.random.randn(10, 10))
plt.figure()
fig, axes = plt.subplots(nrows=1, ncols=2)
df1.plot(ax=axes[0, 0], style='o-')
axes[0, 0].set_xlabel('x')
axes[0, 0].set_ylabel('y')
axes[0, 0].set_title('ttl')
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axes[0, 1].set_ylabel('y')
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However, I get the following error
df1.plot(ax=axes[0, 0], style='o-')
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EDIT: The answer provided below works for 1 row with 2 cols
I'm facing an error for 2 rows and 2 cols
import pandas as pd
import numpy as np
from pprint import pprint
from matplotlib import pyplot as plt
df1 = pd.DataFrame(np.random.randn(10, 10))
df2 = pd.DataFrame(np.random.randn(10, 10))
df3 = pd.DataFrame(np.random.randn(10, 10))
df4 = pd.DataFrame(np.random.randn(10, 10))
pprint(df1)
plt.figure()
fig, axes = plt.subplots(nrows=2, ncols=2)
df1.plot(ax=axes[0], style='o-')
axes[0].set_xlabel('x')
axes[0].set_ylabel('y')
axes[0].set_title('ttl')
df2.plot(ax=axes[1], style='o-')
axes[1].set_xlabel('x')
axes[1].set_ylabel('y')
axes[1].set_title('ttl')
df3.plot(ax=axes[2], style='o-')
axes[2].set_xlabel('x')
axes[2].set_ylabel('y')
axes[2].set_title('ttl')
df4.plot(ax=axes[3], style='o-')
axes[3].set_xlabel('x')
axes[3].set_ylabel('y')
axes[3].set_title('ttl')
plt.show()
Error:
AttributeError: 'numpy.ndarray' object has no attribute 'get_figure'
Any suggestions?
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plot dataframe: overlay line and bar plot doesn't work for time series index?
import numpy as np import pandas as pd import matplotlib.pyplot as plt # create dataframes df0 and df1: index0 = pd.date_range(start='2014-06-01 00:00:00', end='2014-06-01 00:15:00', freq='1S') data0 = np.random.rand(len(index0)) df0 = pd.DataFrame(data=data0, index=index0, columns=['DF0']) index1 = pd.date_range(start='2014-06-01 00:00:00', end='2014-06-01 00:15:00', freq='15S') data1 = np.random.rand(len(index1)) df1 = pd.DataFrame(data=data1, index=index1, columns=['DF1']) # plot df0 and df1: fig,ax1 = plt.subplots(figsize=(40,10)) ax2 = ax1.twinx() df0.plot.line( color="r", ax = ax1) df1.plot.bar( color ='b', linewidth = 5, ax = ax2, alpha = 0.7) plt.show() I can overlay the dataframes as two line plots or as two barplots. But however hard I try, I can't manage to overlay a line plot with a bar plot or the other way round? With the code above I only get the barplot of df1 but don't see the lineplot of df0. What do I have to do differently?
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Pandas to MatPlotLib with Dollar Signs
Given the following data frame:
import pandas as pd
df=pd.DataFrame({'A':['$0-$20','$20+']})
df
A
0 0−20
1 $20+
I'd like to create a bar chart in MatPlotLib but I can't seem to get the dollar signs to show up correctly.
Here's what I have:
import matplotlib.pyplot as plt
import numpy as np
y=df.B
x=df.A
ind=np.arange(len(x))
fig, ax = plt.subplots(1, 1, figsize = (2,2))
plt.bar(ind, y, align='center', width=.5, edgecolor='none', color='grey')
ax.patch.set_facecolor('none')
ax.patch.set_alpha(0)
ax.set_ylim([0,5])
ax.set_xlabel(x,fontsize=12,rotation=0,color='grey')
ax.set_xticklabels('')
ax.set_yticklabels('')
I can get the labels to display "better" if I use df.A.values.tolist(), but that just corrects the format.
I'd like each label to display under each bar with the intended original format (with dollar signs).
Thanks in advance!
To specify the xticklabels, pass tick_label=x to plt.bar.
Matplotlib parses labels using a subset of the TeX markup
language. Dollar
signs indicate the beginning (and end) of math mode. So pairs of bare dollar signs are
getting unintentionally swallowed. Currently, there is no a way to disable mathtex parsing. So to prevent the dollar signs from being interpreted as math markup, replace the
bare $ with \$:
df['A'] = df['A'].str.replace('$', '\$')
For example,
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
df = pd.DataFrame({'A': ['$0-$20', '$20+'], 'B': [10,20]})
df['A'] = df['A'].str.replace('$', '\$')
y = df['B']
x = df['A']
ind = np.arange(len(x))
fig, ax = plt.subplots(1, 1, figsize=(2, 2))
plt.bar(ind, y,
tick_label=x,
align='center', width=.5, edgecolor='none',
color='grey')
plt.show()
Alternatively, you could use df.plot(kind='bar'):
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
df = pd.DataFrame({'A': ['$0-$20', '$20+'], 'B': [10,20]})
df['A'] = df['A'].str.replace('$', '\$')
fig, ax = plt.subplots(1, 1, figsize=(2, 2))
df.plot(kind='bar', x='A', y='B',
align='center', width=.5, edgecolor='none',
color='grey', ax=ax)
plt.xticks(rotation=25)
plt.show()