Transform some kind of exponential distribution into normal distribution
0
I have the following exponential distribution, generated with the following code:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import random
np.random.seed(1)
tags_ratio = np.random.exponential(1/25, 1000)
plt.hist(tags_ratio, range=(0, 1), bins=100)
plt.show()
I'm trying to transform my data, resides in tags_ratio into normal distribution, but with no success.
Tried with the log function and square functions. it given decent results. But I'm interesting in more ideas. Maybe more sophisticated.
python numpy scipy
asked Nov 15 '18 at 8:31
Eran MosheEran Moshe
1,378722
add a comment |
0
I have the following exponential distribution, generated with the following code:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import random
np.random.seed(1)
tags_ratio = np.random.exponential(1/25, 1000)
plt.hist(tags_ratio, range=(0, 1), bins=100)
plt.show()
I'm trying to transform my data, resides in tags_ratio into normal distribution, but with no success.
Tried with the log function and square functions. it given decent results. But I'm interesting in more ideas. Maybe more sophisticated.
python numpy scipy
asked Nov 15 '18 at 8:31
Eran MosheEran Moshe
1,378722
Have you tried log transformation?
– Scratch'N'Purr
Nov 15 '18 at 8:40
Yeah I'm currently doing it with the log.. It's not that normal but it might be sufficient. Anyway I'm interested in more ideas
– Eran Moshe
Nov 15 '18 at 8:41
have you tried with boxcox?
– Dejan Marić
Nov 15 '18 at 8:42
boxcox results doing something similar the sqrt does. It leaves the 0 value hanged high and totally out of the distribution.
– Eran Moshe
Nov 15 '18 at 8:45
add a comment |
0
0
0
0
I have the following exponential distribution, generated with the following code:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import random
np.random.seed(1)
tags_ratio = np.random.exponential(1/25, 1000)
plt.hist(tags_ratio, range=(0, 1), bins=100)
plt.show()
I'm trying to transform my data, resides in tags_ratio into normal distribution, but with no success.
Tried with the log function and square functions. it given decent results. But I'm interesting in more ideas. Maybe more sophisticated.
python numpy scipy
asked Nov 15 '18 at 8:31
Eran MosheEran Moshe
1,378722
I have the following exponential distribution, generated with the following code:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import random
np.random.seed(1)
tags_ratio = np.random.exponential(1/25, 1000)
plt.hist(tags_ratio, range=(0, 1), bins=100)
plt.show()
I'm trying to transform my data, resides in tags_ratio into normal distribution, but with no success.
Tried with the log function and square functions. it given decent results. But I'm interesting in more ideas. Maybe more sophisticated.
python numpy scipy
python numpy scipy
asked Nov 15 '18 at 8:31
Eran MosheEran Moshe
1,378722
asked Nov 15 '18 at 8:31
Eran MosheEran Moshe
1,378722
edited Nov 15 '18 at 8:42
Eran Moshe
asked Nov 15 '18 at 8:31
Eran MosheEran Moshe
1,378722
asked Nov 15 '18 at 8:31
Eran MosheEran Moshe
1,378722
asked Nov 15 '18 at 8:31
Eran MosheEran Moshe
1,378722
1,378722
Have you tried log transformation?
– Scratch'N'Purr
Nov 15 '18 at 8:40
Yeah I'm currently doing it with the log.. It's not that normal but it might be sufficient. Anyway I'm interested in more ideas
– Eran Moshe
Nov 15 '18 at 8:41
have you tried with boxcox?
– Dejan Marić
Nov 15 '18 at 8:42
boxcox results doing something similar the sqrt does. It leaves the 0 value hanged high and totally out of the distribution.
– Eran Moshe
Nov 15 '18 at 8:45
add a comment |
Have you tried log transformation?
– Scratch'N'Purr
Nov 15 '18 at 8:40
Yeah I'm currently doing it with the log.. It's not that normal but it might be sufficient. Anyway I'm interested in more ideas
– Eran Moshe
Nov 15 '18 at 8:41
have you tried with boxcox?
– Dejan Marić
Nov 15 '18 at 8:42
boxcox results doing something similar the sqrt does. It leaves the 0 value hanged high and totally out of the distribution.
– Eran Moshe
Nov 15 '18 at 8:45
Have you tried log transformation?
– Scratch'N'Purr
Nov 15 '18 at 8:40
Have you tried log transformation?
– Scratch'N'Purr
Nov 15 '18 at 8:40
Yeah I'm currently doing it with the log.. It's not that normal but it might be sufficient. Anyway I'm interested in more ideas
– Eran Moshe
Nov 15 '18 at 8:41
Yeah I'm currently doing it with the log.. It's not that normal but it might be sufficient. Anyway I'm interested in more ideas
– Eran Moshe
Nov 15 '18 at 8:41
have you tried with boxcox?
– Dejan Marić
Nov 15 '18 at 8:42
have you tried with boxcox?
– Dejan Marić
Nov 15 '18 at 8:42
boxcox results doing something similar the sqrt does. It leaves the 0 value hanged high and totally out of the distribution.
– Eran Moshe
Nov 15 '18 at 8:45
boxcox results doing something similar the sqrt does. It leaves the 0 value hanged high and totally out of the distribution.
– Eran Moshe
Nov 15 '18 at 8:45
add a comment |
1 Answer
1
active
oldest
votes
1
You can try to see if this helps:
from scipy.stats import boxcox
tags_ratio = boxcox(tags_ratio, 0.3)
plt.hist(tags_ratio)
plt.show()
result:
for more explanations and theory about Box-Cox click here.
answered Nov 15 '18 at 8:44
Dejan MarićDejan Marić
448212
boxcox is nice. I went with log10 but might change it to boxcox when the time is right..
– Eran Moshe
Nov 15 '18 at 11:30
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
1
You can try to see if this helps:
from scipy.stats import boxcox
tags_ratio = boxcox(tags_ratio, 0.3)
plt.hist(tags_ratio)
plt.show()
result:
for more explanations and theory about Box-Cox click here.
answered Nov 15 '18 at 8:44
Dejan MarićDejan Marić
448212
boxcox is nice. I went with log10 but might change it to boxcox when the time is right..
– Eran Moshe
Nov 15 '18 at 11:30
add a comment |
1
You can try to see if this helps:
from scipy.stats import boxcox
tags_ratio = boxcox(tags_ratio, 0.3)
plt.hist(tags_ratio)
plt.show()
result:
for more explanations and theory about Box-Cox click here.
answered Nov 15 '18 at 8:44
Dejan MarićDejan Marić
448212
boxcox is nice. I went with log10 but might change it to boxcox when the time is right..
– Eran Moshe
Nov 15 '18 at 11:30
add a comment |
1
1
1
You can try to see if this helps:
from scipy.stats import boxcox
tags_ratio = boxcox(tags_ratio, 0.3)
plt.hist(tags_ratio)
plt.show()
result:
for more explanations and theory about Box-Cox click here.
answered Nov 15 '18 at 8:44
Dejan MarićDejan Marić
448212
You can try to see if this helps:
from scipy.stats import boxcox
tags_ratio = boxcox(tags_ratio, 0.3)
plt.hist(tags_ratio)
plt.show()
result:
for more explanations and theory about Box-Cox click here.
answered Nov 15 '18 at 8:44
Dejan MarićDejan Marić
448212
answered Nov 15 '18 at 8:44
Dejan MarićDejan Marić
448212
answered Nov 15 '18 at 8:44
Dejan MarićDejan Marić
448212
answered Nov 15 '18 at 8:44
Dejan MarićDejan Marić
448212
448212
boxcox is nice. I went with log10 but might change it to boxcox when the time is right..
– Eran Moshe
Nov 15 '18 at 11:30
add a comment |
boxcox is nice. I went with log10 but might change it to boxcox when the time is right..
– Eran Moshe
Nov 15 '18 at 11:30
boxcox is nice. I went with log10 but might change it to boxcox when the time is right..
– Eran Moshe
Nov 15 '18 at 11:30
boxcox is nice. I went with log10 but might change it to boxcox when the time is right..
– Eran Moshe
Nov 15 '18 at 11:30
add a comment |
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Have you tried log transformation?
– Scratch'N'Purr
Nov 15 '18 at 8:40
Yeah I'm currently doing it with the log.. It's not that normal but it might be sufficient. Anyway I'm interested in more ideas
– Eran Moshe
Nov 15 '18 at 8:41
have you tried with boxcox?
– Dejan Marić
Nov 15 '18 at 8:42
boxcox results doing something similar the sqrt does. It leaves the 0 value hanged high and totally out of the distribution.
– Eran Moshe
Nov 15 '18 at 8:45