Scatter Plot and missing values
I'm very new to python and I'm experimenting with matplotlib.pyplot.
I'm plotting my data using a scatter plot. What I could see from the descriptive statistics all of my columns have 1/4 of missing values.
So my question is how does a scatter plot treats missing values?
does it ignore them (excluding them from the plot)
or
it replaces the values by 0?
Thanks in advance.
python matplotlib missing-data
add a comment |
I'm very new to python and I'm experimenting with matplotlib.pyplot.
I'm plotting my data using a scatter plot. What I could see from the descriptive statistics all of my columns have 1/4 of missing values.
So my question is how does a scatter plot treats missing values?
does it ignore them (excluding them from the plot)
or
it replaces the values by 0?
Thanks in advance.
python matplotlib missing-data
add a comment |
I'm very new to python and I'm experimenting with matplotlib.pyplot.
I'm plotting my data using a scatter plot. What I could see from the descriptive statistics all of my columns have 1/4 of missing values.
So my question is how does a scatter plot treats missing values?
does it ignore them (excluding them from the plot)
or
it replaces the values by 0?
Thanks in advance.
python matplotlib missing-data
I'm very new to python and I'm experimenting with matplotlib.pyplot.
I'm plotting my data using a scatter plot. What I could see from the descriptive statistics all of my columns have 1/4 of missing values.
So my question is how does a scatter plot treats missing values?
does it ignore them (excluding them from the plot)
or
it replaces the values by 0?
Thanks in advance.
python matplotlib missing-data
python matplotlib missing-data
asked Nov 21 '18 at 10:59
Chrissie M.Chrissie M.
334
334
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1 Answer
1
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votes
If there are nan
they are not plotted.
Example:
x = [1,2,3,4,5]
y = [1,np.nan,np.nan, 3, 4]
plt.scatter(x, y)
plt.xlabel('x')
plt.ylabel('y')
plt.show()
On the contrary with y = [1,0,0,3,4]
:
Of course you can replace the nan
with 0
or other values. The 'how' depends the kind of your data. For list:
import math
y = [0 if math.isnan(e) else e for e in y]
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
If there are nan
they are not plotted.
Example:
x = [1,2,3,4,5]
y = [1,np.nan,np.nan, 3, 4]
plt.scatter(x, y)
plt.xlabel('x')
plt.ylabel('y')
plt.show()
On the contrary with y = [1,0,0,3,4]
:
Of course you can replace the nan
with 0
or other values. The 'how' depends the kind of your data. For list:
import math
y = [0 if math.isnan(e) else e for e in y]
add a comment |
If there are nan
they are not plotted.
Example:
x = [1,2,3,4,5]
y = [1,np.nan,np.nan, 3, 4]
plt.scatter(x, y)
plt.xlabel('x')
plt.ylabel('y')
plt.show()
On the contrary with y = [1,0,0,3,4]
:
Of course you can replace the nan
with 0
or other values. The 'how' depends the kind of your data. For list:
import math
y = [0 if math.isnan(e) else e for e in y]
add a comment |
If there are nan
they are not plotted.
Example:
x = [1,2,3,4,5]
y = [1,np.nan,np.nan, 3, 4]
plt.scatter(x, y)
plt.xlabel('x')
plt.ylabel('y')
plt.show()
On the contrary with y = [1,0,0,3,4]
:
Of course you can replace the nan
with 0
or other values. The 'how' depends the kind of your data. For list:
import math
y = [0 if math.isnan(e) else e for e in y]
If there are nan
they are not plotted.
Example:
x = [1,2,3,4,5]
y = [1,np.nan,np.nan, 3, 4]
plt.scatter(x, y)
plt.xlabel('x')
plt.ylabel('y')
plt.show()
On the contrary with y = [1,0,0,3,4]
:
Of course you can replace the nan
with 0
or other values. The 'how' depends the kind of your data. For list:
import math
y = [0 if math.isnan(e) else e for e in y]
edited Nov 21 '18 at 12:37
answered Nov 21 '18 at 12:30
JoeJoe
6,08421430
6,08421430
add a comment |
add a comment |
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