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Question about autocorrelation_plot result vs autocorr result
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I used autocorrelation_plot to plot the autocorrelation of a straight line:
import numpy as np
import pandas as pd
from pandas.plotting import autocorrelation_plot
import matplotlib.pyplot as plt
dr = pd.date_range(start='1984-01-01', end='1984-12-31')
df = pd.DataFrame(np.arange(len(dr)), index=dr, columns=["Values"])
autocorrelation_plot(df)
plt.show()
Then, I tried using autocorr() to calculate the autocorrelation with different lags:
for i in range(0,366):
print(df['Values'].autocorr(lag=i))
The output is 1 (or 0.99) for all the lag. But it is clear from the correlogram that the autocorrelation is a curve rather than a straight line fixed at 1.
Did I interpret the correlogram incorrectly or did I use the autocorr() function incorrectly? Thanks!
python pandas autocorrelation
asked Jan 3 at 7:15
ChengCheng
6,39784070
add a comment |
I used autocorrelation_plot to plot the autocorrelation of a straight line:
import numpy as np
import pandas as pd
from pandas.plotting import autocorrelation_plot
import matplotlib.pyplot as plt
dr = pd.date_range(start='1984-01-01', end='1984-12-31')
df = pd.DataFrame(np.arange(len(dr)), index=dr, columns=["Values"])
autocorrelation_plot(df)
plt.show()
Then, I tried using autocorr() to calculate the autocorrelation with different lags:
for i in range(0,366):
print(df['Values'].autocorr(lag=i))
The output is 1 (or 0.99) for all the lag. But it is clear from the correlogram that the autocorrelation is a curve rather than a straight line fixed at 1.
Did I interpret the correlogram incorrectly or did I use the autocorr() function incorrectly? Thanks!
python pandas autocorrelation
asked Jan 3 at 7:15
ChengCheng
6,39784070
add a comment |
I used autocorrelation_plot to plot the autocorrelation of a straight line:
import numpy as np
import pandas as pd
from pandas.plotting import autocorrelation_plot
import matplotlib.pyplot as plt
dr = pd.date_range(start='1984-01-01', end='1984-12-31')
df = pd.DataFrame(np.arange(len(dr)), index=dr, columns=["Values"])
autocorrelation_plot(df)
plt.show()
Then, I tried using autocorr() to calculate the autocorrelation with different lags:
for i in range(0,366):
print(df['Values'].autocorr(lag=i))
The output is 1 (or 0.99) for all the lag. But it is clear from the correlogram that the autocorrelation is a curve rather than a straight line fixed at 1.
Did I interpret the correlogram incorrectly or did I use the autocorr() function incorrectly? Thanks!
python pandas autocorrelation
asked Jan 3 at 7:15
ChengCheng
6,39784070
I used autocorrelation_plot to plot the autocorrelation of a straight line:
import numpy as np
import pandas as pd
from pandas.plotting import autocorrelation_plot
import matplotlib.pyplot as plt
dr = pd.date_range(start='1984-01-01', end='1984-12-31')
df = pd.DataFrame(np.arange(len(dr)), index=dr, columns=["Values"])
autocorrelation_plot(df)
plt.show()
Then, I tried using autocorr() to calculate the autocorrelation with different lags:
for i in range(0,366):
print(df['Values'].autocorr(lag=i))
The output is 1 (or 0.99) for all the lag. But it is clear from the correlogram that the autocorrelation is a curve rather than a straight line fixed at 1.
Did I interpret the correlogram incorrectly or did I use the autocorr() function incorrectly? Thanks!
python pandas autocorrelation
python pandas autocorrelation
asked Jan 3 at 7:15
ChengCheng
6,39784070
asked Jan 3 at 7:15
ChengCheng
6,39784070
edited Jan 3 at 10:22
Cheng
asked Jan 3 at 7:15
ChengCheng
6,39784070
asked Jan 3 at 7:15
ChengCheng
6,39784070
asked Jan 3 at 7:15
ChengCheng
6,39784070
6,39784070
add a comment |
add a comment |
1 Answer
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You are using both functions correctly, but... Autocorrelation_plot uses a different way of calculating autocorrelations then autocorr() does.
The following two posts explain more about the differences. Unfortunately I don't know which way of calculating is the correct way:
What's the difference between pandas ACF and statsmodel ACF?
Why NUMPY correlate and corrcoef return different values and how to "normalize" a correlate in "full" mode?
If you need it, you can get the autocorrelations out of your autocorrelation plot as follows:
ax = autocorrelation_plot(df)
ax.lines[5].get_data()[1]
answered Jan 3 at 12:43
Sander van den OordSander van den Oord
715520
Thanks for the links. From what I can tell,autocorr()callednp.corrcoef()which calculates the pearson correlation, which is different from autocomplete correlation. The implementation ofautocorrelation_plotis correct. I have submitted an issue on github.
– Cheng
Jan 4 at 8:54
add a comment |
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1 Answer
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active
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1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
You are using both functions correctly, but... Autocorrelation_plot uses a different way of calculating autocorrelations then autocorr() does.
The following two posts explain more about the differences. Unfortunately I don't know which way of calculating is the correct way:
What's the difference between pandas ACF and statsmodel ACF?
Why NUMPY correlate and corrcoef return different values and how to "normalize" a correlate in "full" mode?
If you need it, you can get the autocorrelations out of your autocorrelation plot as follows:
ax = autocorrelation_plot(df)
ax.lines[5].get_data()[1]
answered Jan 3 at 12:43
Sander van den OordSander van den Oord
715520
Thanks for the links. From what I can tell,autocorr()callednp.corrcoef()which calculates the pearson correlation, which is different from autocomplete correlation. The implementation ofautocorrelation_plotis correct. I have submitted an issue on github.
– Cheng
Jan 4 at 8:54
add a comment |
You are using both functions correctly, but... Autocorrelation_plot uses a different way of calculating autocorrelations then autocorr() does.
The following two posts explain more about the differences. Unfortunately I don't know which way of calculating is the correct way:
What's the difference between pandas ACF and statsmodel ACF?
Why NUMPY correlate and corrcoef return different values and how to "normalize" a correlate in "full" mode?
If you need it, you can get the autocorrelations out of your autocorrelation plot as follows:
ax = autocorrelation_plot(df)
ax.lines[5].get_data()[1]
answered Jan 3 at 12:43
Sander van den OordSander van den Oord
715520
Thanks for the links. From what I can tell,autocorr()callednp.corrcoef()which calculates the pearson correlation, which is different from autocomplete correlation. The implementation ofautocorrelation_plotis correct. I have submitted an issue on github.
– Cheng
Jan 4 at 8:54
add a comment |
You are using both functions correctly, but... Autocorrelation_plot uses a different way of calculating autocorrelations then autocorr() does.
The following two posts explain more about the differences. Unfortunately I don't know which way of calculating is the correct way:
What's the difference between pandas ACF and statsmodel ACF?
Why NUMPY correlate and corrcoef return different values and how to "normalize" a correlate in "full" mode?
If you need it, you can get the autocorrelations out of your autocorrelation plot as follows:
ax = autocorrelation_plot(df)
ax.lines[5].get_data()[1]
answered Jan 3 at 12:43
Sander van den OordSander van den Oord
715520
You are using both functions correctly, but... Autocorrelation_plot uses a different way of calculating autocorrelations then autocorr() does.
The following two posts explain more about the differences. Unfortunately I don't know which way of calculating is the correct way:
What's the difference between pandas ACF and statsmodel ACF?
Why NUMPY correlate and corrcoef return different values and how to "normalize" a correlate in "full" mode?
If you need it, you can get the autocorrelations out of your autocorrelation plot as follows:
ax = autocorrelation_plot(df)
ax.lines[5].get_data()[1]
answered Jan 3 at 12:43
Sander van den OordSander van den Oord
715520
edited Jan 3 at 12:50
answered Jan 3 at 12:43
Sander van den OordSander van den Oord
715520
answered Jan 3 at 12:43
Sander van den OordSander van den Oord
715520
answered Jan 3 at 12:43
Sander van den OordSander van den Oord
715520
715520
Thanks for the links. From what I can tell,autocorr()callednp.corrcoef()which calculates the pearson correlation, which is different from autocomplete correlation. The implementation ofautocorrelation_plotis correct. I have submitted an issue on github.
– Cheng
Jan 4 at 8:54
add a comment |
Thanks for the links. From what I can tell,autocorr()callednp.corrcoef()which calculates the pearson correlation, which is different from autocomplete correlation. The implementation ofautocorrelation_plotis correct. I have submitted an issue on github.
– Cheng
Jan 4 at 8:54
Thanks for the links. From what I can tell,
autocorr() called np.corrcoef() which calculates the pearson correlation, which is different from autocomplete correlation. The implementation of autocorrelation_plot is correct. I have submitted an issue on github.– Cheng
Jan 4 at 8:54
Thanks for the links. From what I can tell,
autocorr() called np.corrcoef() which calculates the pearson correlation, which is different from autocomplete correlation. The implementation of autocorrelation_plot is correct. I have submitted an issue on github.– Cheng
Jan 4 at 8:54
add a comment |
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