subplotting different dataframes and using a dataframe as the x value - python-3.x
I have dataFrame which I obtain from a CSV file that contains a column which is the Time and 18 columns that are samples taken in that time. The first thing I do is to calculate the mean for each replicate and create three different data frame. with the following code:
data = pd.read_csv('growht.csv', delimiter=',', header=0)
file:
# read the following data in with
data = pd.read_clipboard(sep=',', index=False)
Time,WT5,WT5,WT5,WT1,WT1,WT1,NF5,NF5,NF5,NF1,NF1,NF1,D5,D5,D5,D1,D1,D1
9.7e-05,0.113,0.11900000000000001,0.11699999999999999,0.081,0.086,0.076,0.102,0.111,0.111,0.086,0.087,0.084,0.1,0.105,0.106,0.085,0.087,0.086
0.041737,0.122,0.121,0.126,0.075,0.07400000000000001,0.07400000000000001,0.10400000000000001,0.105,0.10300000000000001,0.075,0.073,0.073,0.1,0.09699999999999999,0.09699999999999999,0.075,0.073,0.073
0.08340299999999999,0.161,0.163,0.174,0.076,0.075,0.075,0.126,0.129,0.13,0.076,0.07400000000000001,0.07400000000000001,0.12,0.11900000000000001,0.11900000000000001,0.076,0.07400000000000001,0.07400000000000001
0.12507200000000002,0.285,0.307,0.303,0.079,0.079,0.079,0.175,0.188,0.191,0.077,0.07400000000000001,0.075,0.165,0.17,0.172,0.079,0.077,0.077
0.166738,0.34600000000000003,0.368,0.369,0.09,0.091,0.091,0.273,0.28300000000000003,0.292,0.078,0.076,0.077,0.255,0.27,0.278,0.08800000000000001,0.085,0.085
0.208404,0.418,0.461,0.418,0.113,0.122,0.121,0.366,0.41200000000000003,0.38,0.08,0.078,0.079,0.368,0.376,0.382,0.113,0.10400000000000001,0.106
0.25007399999999996,0.48,0.513,0.508,0.18,0.2,0.196,0.418,0.42100000000000004,0.43,0.08800000000000001,0.087,0.08900000000000001,0.446,0.47700000000000004,0.475,0.17300000000000001,0.155,0.158
0.29173699999999997,0.551,0.589,0.5920000000000001,0.311,0.33399999999999996,0.336,0.46399999999999997,0.47600000000000003,0.47,0.10400000000000001,0.105,0.10800000000000001,0.5379999999999999,0.544,0.542,0.24,0.22699999999999998,0.22699999999999998
0.3334,0.612,0.603,0.617,0.436,0.48100000000000004,0.446,0.514,0.556,0.53,0.14,0.147,0.154,0.59,0.644,0.629,0.361,0.35100000000000003,0.341
0.375066,0.682,0.685,0.703,0.516,0.505,0.47600000000000003,0.5670000000000001,0.605,0.5760000000000001,0.215,0.247,0.259,0.6559999999999999,0.72,0.735,0.456,0.41200000000000003,0.409
0.416733,0.7340000000000001,0.741,0.755,0.735,0.624,0.605,0.609,0.614,0.588,0.335,0.355,0.365,0.708,0.746,0.7490000000000001,0.523,0.495,0.494
0.4584,0.763,0.799,0.8420000000000001,0.748,0.682,0.6659999999999999,0.653,0.6759999999999999,0.655,0.42200000000000004,0.442,0.45299999999999996,0.759,0.809,0.81,0.629,0.5870000000000001,0.59
0.500066,0.802,0.858,0.8740000000000001,0.831,0.767,0.757,0.6809999999999999,0.705,0.684,0.47100000000000003,0.47,0.47200000000000003,0.816,0.863,0.8690000000000001,0.645,0.632,0.645
0.541733,0.852,0.893,0.903,0.863,0.748,0.731,0.7170000000000001,0.741,0.722,0.562,0.579,0.5760000000000001,0.872,0.927,0.9279999999999999,0.7070000000000001,0.675,0.6729999999999999
0.583399,0.927,0.907,0.9840000000000001,0.889,0.773,0.742,0.74,0.763,0.741,0.614,0.66,0.64,0.914,0.975,0.975,0.7290000000000001,0.698,0.693
0.625066,0.9590000000000001,0.956,1.041,0.892,0.7829999999999999,0.746,0.762,0.78,0.767,0.647,0.711,0.693,0.95,1.02,1.016,0.76,0.745,0.742
0.666733,0.987,1.04,1.035,0.8909999999999999,0.7959999999999999,0.807,0.769,0.7959999999999999,0.7859999999999999,0.7,0.731,0.718,0.978,1.058,1.047,0.789,0.782,0.782
0.708399,1.042,1.056,1.032,0.848,0.802,0.833,0.777,0.81,0.7979999999999999,0.737,0.782,0.775,0.9790000000000001,1.083,1.075,0.807,0.818,0.8170000000000001
0.750067,1.062,1.0979999999999999,1.0590000000000002,0.8540000000000001,0.8590000000000001,0.8490000000000001,0.785,0.815,0.8079999999999999,0.7929999999999999,0.828,0.804,0.973,1.102,1.091,0.831,0.851,0.85
0.791732,1.0959999999999999,1.102,1.069,0.8590000000000001,0.941,0.889,0.7709999999999999,0.802,0.797,0.809,0.853,0.825,0.956,1.0979999999999999,1.0859999999999999,0.836,0.875,0.872
0.8334,1.125,1.133,1.1,0.8690000000000001,0.9790000000000001,0.932,0.757,0.795,0.7909999999999999,0.835,0.884,0.8440000000000001,0.945,1.103,1.085,0.843,0.8859999999999999,0.889
0.875065,1.133,1.166,1.121,0.89,0.9990000000000001,0.975,0.7440000000000001,0.7829999999999999,0.7809999999999999,0.843,0.898,0.855,0.938,1.097,1.074,0.836,0.8959999999999999,0.8959999999999999
0.916733,1.136,1.198,1.119,0.92,1.056,0.9540000000000001,0.727,0.777,0.773,0.853,0.905,0.858,0.917,1.088,1.07,0.8220000000000001,0.8959999999999999,0.898
0.9584,1.119,1.202,1.115,0.9179999999999999,1.071,1.026,0.7140000000000001,0.7609999999999999,0.76,0.851,0.907,0.8490000000000001,0.904,1.075,1.055,0.812,0.8859999999999999,0.8909999999999999
1.000065,1.167,1.199,1.099,0.9079999999999999,1.093,1.006,0.6970000000000001,0.748,0.7509999999999999,0.835,0.902,0.843,0.889,1.069,1.0490000000000002,0.8009999999999999,0.885,0.892
data.columns = data.columns.str.replace('(\.\d+)$','') #with this I remove the .N when the columns has the same name
data_mean=data.mean(axis=1, level=0)#calculates the mean of the columns with the same name in the row axis
data_std=data.std(axis=1, level=0)
data_time=data.filter(like='Time')
data_WT=data_mean.filter(like='WT')
data_NF=data_mean.filter(like='NF')
data_D=data_mean.filter(like='D')
now with the code above I create new dataframes that only contains the columns with specific titles. So I have three different dataFrames with 2 columns and 24 rows each. Which I manage to plot them in the same figure using the following code:
fig, axes = plt.subplots(nrows=1, ncols=3,squeeze=False,figsize=(10,5))
axes = axes.flatten()
data_WT.plot(ax=axes[0],yerr=data_std,fontsize=6,grid=True)
data_NF.plot(ax=axes[1],yerr=data_std,fontsize=6,grid=True)
data_D.plot(ax=axes[2],yerr=data_std,fontsize=6,grid=True)
the output look like this:
then I wanted to add scatter for each point in each graph for every point. For this I add the dataFrame data_time that contains the values of the time to use it as the x value in the scatter plot. However when I do this for the first subplot for example:
data_WT.plot.scatter(ax=axes[0],x=data_time,y=data_WT)
I have the following error:
Traceback (most recent call last):
File "c:/Users/Nico/Desktop/bioscreen.py", line 60, in <module>
data_WT.plot.scatter(ax=axes[0],x=data_time,y=data_WT)
File "C:\Users\Nico\AppData\Local\Programs\Python\Python38\lib\site-packages\pandas\plotting\_core.py", line 1499, in scatter
return self(kind="scatter", x=x, y=y, s=s, c=c, **kwargs)
File "C:\Users\Nico\AppData\Local\Programs\Python\Python38\lib\site-packages\pandas\plotting\_core.py", line 792, in __call__
return plot_backend.plot(data, x=x, y=y, kind=kind, **kwargs)
File "C:\Users\Nico\AppData\Local\Programs\Python\Python38\lib\site-packages\pandas\plotting\_matplotlib\__init__.py", line 61, in plot
plot_obj.generate()
File "C:\Users\Nico\AppData\Local\Programs\Python\Python38\lib\site-packages\pandas\plotting\_matplotlib\core.py", line 263, in generate
self._make_plot()
File "C:\Users\Nico\AppData\Local\Programs\Python\Python38\lib\site-packages\pandas\plotting\_matplotlib\core.py", line 970, in _make_plot
data[x].values,
File "C:\Users\Nico\AppData\Local\Programs\Python\Python38\lib\site-packages\pandas\core\frame.py", line 2806, in __getitem__
indexer = self.loc._get_listlike_indexer(key, axis=1, raise_missing=True)[1]
File "C:\Users\Nico\AppData\Local\Programs\Python\Python38\lib\site-packages\pandas\core\indexing.py", line 1551, in _get_listlike_indexer
self._validate_read_indexer(
File "C:\Users\Nico\AppData\Local\Programs\Python\Python38\lib\site-packages\pandas\core\indexing.py", line 1639, in _validate_read_indexer
raise KeyError(f"None of [{key}] are in the [{axis_name}]")
KeyError: "None of [Float64Index([ 9.73e-05, 0.041736991, 0.083402986,\n 0.125072396, 0.166737708, 0.20840449100000003,\n 0.250073843, 0.29173736100000003, 0.333400081,\n 0.375066481, 0.41673263899999996, 0.458399595,\n 0.500066227,
0.541732743, 0.583399375,\n 0.625065949, 0.666732685, 0.7083994790000001,\n
0.75006728, 0.79173228, 0.833399606,\n 0.875064988, 0.916732766, 0.958400093,\n 1.000065417],\n dtype='float64')] are in the [columns]"
Any suggestion in how to overcome this error, I have been reading but I can't make any answer to help me with this.
Thank you.
It's easiest to resolve the issue by setting Time as the index.
Also using seaborn.scatterplot is easier to add the scatter plot.
Seaborn is a Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics.
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
# read the file in with Time as the index
data = pd.read_csv('growth.csv', delimiter=',', header=0, index_col='Time')
# change the column names
data.columns = data.columns.str.replace('(\.\d+)$','')
# don't change any of this code, but data_time isn't needed
data_mean=data.mean(axis=1, level=0)
data_std=data.std(axis=1, level=0)
data_WT=data_mean.filter(like='WT')
data_NF=data_mean.filter(like='NF')
data_D=data_mean.filter(like='D')
# plot
fig, axes = plt.subplots(nrows=1, ncols=3, squeeze=False, figsize=(16, 8))
axes = axes.flatten()
data_WT.plot(ax=axes[0],yerr=data_std,fontsize=6,grid=True)
sns.scatterplot(data=data_WT, ax=axes[0])
data_NF.plot(ax=axes[1],yerr=data_std,fontsize=6,grid=True)
sns.scatterplot(data=data_NF, ax=axes[1])
data_D.plot(ax=axes[2],yerr=data_std,fontsize=6,grid=True)
sns.scatterplot(data=data_D, ax=axes[2])
If all you're trying to accomplish with the scatter plot is to add the markers to the plot, then you can use the marker parameter when making each plot
fig, axes = plt.subplots(nrows=1, ncols=3, squeeze=False, figsize=(16, 8))
axes = axes.flatten()
data_WT.plot(ax=axes[0],yerr=data_std,fontsize=6,grid=True, marker='o')
data_NF.plot(ax=axes[1],yerr=data_std,fontsize=6,grid=True, marker='o')
data_D.plot(ax=axes[2],yerr=data_std,fontsize=6,grid=True, marker='o')
Related
Bar plot with different minimal value for each bar
I'm trying to reproduce this type of graph :
basically, the Y axis represent the date of beginning and end of a phenomenon for each year.
but here is what I have when I try to plot my data :
It seems that no matter what, the bar for each year is plotted from the y axis minimal value.
Here is the data I use
Here is my code :
select=pd.read_excel("./writer.xlsx")
select=pd.DataFrame(select)
select["dte"]=pd.to_datetime(select.dte)
select["month_day"]=pd.DatetimeIndex(select.dte).strftime('%B %d')
select["month"]=pd.DatetimeIndex(select.dte).month
select["day"]=pd.DatetimeIndex(select.dte).day
gs=gridspec.GridSpec(2,2)
fig=plt.figure()
ax1=plt.subplot(gs[0,0])
ax2=plt.subplot(gs[0,1])
ax3=plt.subplot(gs[1,:])
###2 others graphs that works just fine
data=pd.DataFrame()
del select["res"],select["Seuil"],select["Seuil%"] #these don't matter for that graph
for year_ in list(set(select.dteYear)):
temp=select.loc[select["dteYear"]==year_]
temp2=temp.iloc[[0,-1]] #the beginning and ending of the phenomenon
data=pd.concat([data,temp2]).reset_index(drop=True)
data=data.sort_values(["month","day"])
ax3.bar(data["dteYear"],data["month_day"],tick_label=data["dteYear"])
plt.show()
If you have some clue to help me, I'd really appreciate, because I havn't found any model to make this type of graph.
thanks !
EDIT :
I tried something else :
height,bottom,x_position=[], [], []
for year_ in list(set(select.dteYear)):
temp=select.loc[select["dteYear"]==year_]
bottom.append(temp["month_day"].iloc[0])
height.append(temp["month_day"].iloc[-1])
x_position.append(year_)
temp2=temp.iloc[[0,-1]]
data=pd.concat([data,temp2]).reset_index(drop=True)
ax3.bar(x=x_position,height=height,bottom=bottom,tick_label=x_position)
I got this error :
Traceback (most recent call last):
File "C:\Users\E31\Documents\cours\stage_dossier\projet_python\tool_etiage\test.py", line 103, in <module>
ax3.bar(x=x_position,height=height,bottom=bottom,tick_label=x_position)
File "C:\Users\E31\AppData\Local\Programs\Python\Python39\lib\site-packages\matplotlib\__init__.py", line 1352, in inner
return func(ax, *map(sanitize_sequence, args), **kwargs)
File "C:\Users\E31\AppData\Local\Programs\Python\Python39\lib\site-packages\matplotlib\axes\_axes.py", line 2357, in bar
r = mpatches.Rectangle(
File "C:\Users\E31\AppData\Local\Programs\Python\Python39\lib\site-packages\matplotlib\patches.py", line 752, in __init__
super().__init__(**kwargs)
File "C:\Users\E31\AppData\Local\Programs\Python\Python39\lib\site-packages\matplotlib\patches.py", line 101, in __init__
self.set_linewidth(linewidth)
File "C:\Users\E31\AppData\Local\Programs\Python\Python39\lib\site-packages\matplotlib\patches.py", line 406, in set_linewidth
self._linewidth = float(w)
TypeError: only size-1 arrays can be converted to Python scalars
To make a bar graph that shows a difference between dates you should start by getting your data into a nice format in the dataframe where it is easy to access the bottom and top values of the bar for each year you are plotting. After this you can simply plot the bars and indicate the 'bottom' parameter. The hardest part in your case may be specifying the datetime differences correctly. I added a x tick locator and y tick formatter for the datetimes.
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import matplotlib as mpl
import matplotlib.dates as mdates
# make function that returns a random datetime
# between a start and stop date
def random_date(start, stop):
days = (stop - start).days
rand = np.random.randint(days)
return start + pd.Timedelta(rand, unit='days')
# simulate poster's data
T1 = pd.to_datetime('July 1 2021')
T2 = pd.to_datetime('August 1 2021')
T3 = pd.to_datetime('November 1 2021')
df = pd.DataFrame({
'year' : np.random.choice(np.arange(1969, 2020), size=15, replace=False),
'bottom' : [random_date(T1, T2) for x in range(15)],
'top' : [random_date(T2, T3) for x in range(15)],
}).sort_values(by='year').set_index('year')
# define fig/ax and figsize
fig, ax = plt.subplots(figsize=(16,8))
# plot data
ax.bar(
x = df.index,
height = (df.top - df.bottom),
bottom = df.bottom,
color = '#9e7711'
)
# add x_locator (every 2 years), y tick datetime formatter, grid
# hide top/right spines, and rotate the x ticks for readability
x_locator = ax.xaxis.set_major_locator(mpl.ticker.MultipleLocator(2))
y_formatter = ax.yaxis.set_major_formatter(mdates.DateFormatter('%d %b'))
tick_params = ax.tick_params(axis='x', rotation=45)
grid = ax.grid(axis='y', dashes=(8,3), alpha=0.3, color='gray')
hide_spines = [ax.spines[s].set_visible(False) for s in ['top','right']]
Secondary y-axis using seaborn
I am trying to plot a bar chart and a line chart as a single plot and inclined to use seaborn due to its nice formatting features. However, when I do df1.plot(kind='bar',...) followed by df1.plot(kind='line',..., secondary_y=True), I get similar outcome as below, i.e., no line chart but no error.
import seaborn as sns
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
# Sample dataframe.
df1 = pd.DataFrame({'date':pd.date_range(datetime(2020,1,1), periods=699).tolist(), 'amount':range(1,700), 'balance':np.cumsum(range(1,700))})
df1.loc[:, 'month'] = df1['date'].dt.to_period("M")
df1.loc[:, 'month_str'] = df1['date'].dt.year.astype(str) + '-' + df1['date'].dt.month.astype(str)
df1.loc[:, 'month_dt'] = pd.to_datetime(df1.month.dt.year*10000+df1.month.dt.month*100+1,format='%Y%m%d')
# Case-1: This doesn't work.
df2 = df1.groupby(['month']).agg({'amount':'sum','balance':'sum'})
sns.barplot(x='month', y='amount', data=df2.reset_index(), palette="Blues_d")
ax2 = plt.twinx()
sns.lineplot(x='month', y='balance', data=df2.reset_index(), color='red', markers=True, ax=ax2)
# Case-2: This doesn't work (as intended, if months grow they will not auto-adjust max numbers to show and not sorted).
df2 = df1.groupby(['month_str']).agg({'amount':'sum','balance':'sum'})
sns.barplot(x='month_str', y='amount', data=df2.reset_index(), palette="Blues_d")
ax2 = plt.twinx()
sns.lineplot(x='month_str', y='balance', data=df2.reset_index(), color='red', markers=True, ax=ax2)
# Case-3: This doesn't work either.
df2 = df1.groupby(['month_dt']).agg({'amount':'sum','balance':'sum'})
sns.barplot(x='month_dt', y='amount', data=df2.reset_index(), palette="Blues_d")
ax2 = plt.twinx()
sns.lineplot(x='month_dt', y='balance', data=df2.reset_index(), color='red', markers=True, ax=ax2)
Case-1:
Traceback (most recent call last):
File "C:\...\lib\site-packages\seaborn\_decorators.py", line 46, in inner_f
return f(**kwargs)
File "C:\...\lib\site-packages\seaborn\relational.py", line 703, in lineplot
p.plot(ax, kwargs)
File "C:\...\lib\site-packages\seaborn\relational.py", line 529, in plot
line, = ax.plot(x, y, **kws)
File "C:\...\lib\site-packages\matplotlib\axes\_axes.py", line 1745, in plot
self.add_line(line)
File "C:\...\lib\site-packages\matplotlib\axes\_base.py", line 1964, in add_line
self._update_line_limits(line)
File "C:\...\lib\site-packages\matplotlib\axes\_base.py", line 1986, in _update_line_limits
path = line.get_path()
File "C:\...\lib\site-packages\matplotlib\lines.py", line 1011, in get_path
self.recache()
File "C:\...\lib\site-packages\matplotlib\lines.py", line 653, in recache
x = _to_unmasked_float_array(xconv).ravel()
File "C:\...\lib\site-packages\matplotlib\cbook\__init__.py", line 1289, in _to_unmasked_float_array
return np.asarray(x, float)
File "C:\...\lib\site-packages\numpy\core\_asarray.py", line 83, in asarray
return array(a, dtype, copy=False, order=order)
TypeError: float() argument must be a string or a number, not 'Period'
Case-2:
Case-3:
You can build a dummy x axis and replace the values with the month data after constructing the plot:
fig, ax = plt.subplots()
df2 = df1.groupby(['month']).agg({'amount':'sum','balance':'sum'})
# helper axis
data = df2.reset_index()
data['xaxis'] = range(len(data))
sns.barplot(x='xaxis', y='amount', data=data, palette="Blues_d", ax=ax)
ax2 = ax.twinx()
sns.lineplot(x='xaxis', y='balance', data=data, color='red', markers=True, ax=ax2)
# replace helper axis with actual data
ax.set_xticklabels(data['month'].values, rotation = 45, ha="right")
You don't need to create a dummy x axis. Try the following code:
import seaborn as sns
import pandas as pd
import numpy as np
# Sample dataframe.
df1 = pd.DataFrame({'date':pd.date_range(pd.datetime(2020,1,1), periods=699).tolist(), 'amount':range(1,700), 'balance':np.cumsum(range(1,700))})
df1.loc[:, 'month'] = df1['date'].dt.to_period("M")
df2 = df1.groupby(['month']).agg({'amount':'sum','balance':'sum'})
g = sns.barplot(x='month', y='amount', data=df2.reset_index(), palette="Blues_d")
g.set_xticklabels(g.get_xticklabels(), rotation=90)
sns.lineplot(x=range(len(df2.reset_index())), y='balance', data=df2.reset_index(), color='red', markers=True, ax=g.twinx())
Error when drawing a legend on a separate plot
I want to plot a legend on a separate frame than the original plot. I can plot the legend from plot commands. But not the legend from fill_between.
Here is a sample code
#!/usr/bin/env python
import numpy as np
import matplotlib.pyplot as plt
xx = np.linspace(0, 3.14*3, 100)
yy = np.sin (xx)
zz = yy +0.5
# I can draw a plot with legend
fig = plt.figure( )
ax = fig.add_subplot(1, 1, 1,)
line1, = ax.plot (xx, yy, label='xx')
line2, = ax.plot (xx, zz, label='yy')
fill0 = ax.fill_between (xx, yy, zz, label='filling', alpha=0.2, color='grey' )
ax.legend ( handles=[line1, line2, fill0])
plt.show()
# I can draw a empty plot with the legend of the lines
plt.legend(handles=[line1, line2])
plt.show()
# I can't draw an empty plot with the legend of the fill
# Why ?
# Can I fix this ?
plt.legend(handles=[fill0,])
plt.show()
And now the error :
Traceback (most recent call last):
File "Untitled.py", line 34, in <module>
plt.legend(handles=[fill0,])
File "/Users/marti/anaconda3/envs/PROD/lib/python3.7/site-packages/matplotlib/pyplot.py", line 2721, in legend
return gca().legend(*args, **kwargs)
File "/Users/marti/anaconda3/envs/PROD/lib/python3.7/site-packages/matplotlib/axes/_axes.py", line 417, in legend
self.legend_ = mlegend.Legend(self, handles, labels, **kwargs)
File "/Users/marti/anaconda3/envs/PROD/lib/python3.7/site-packages/matplotlib/legend.py", line 503, in __init__
self._init_legend_box(handles, labels, markerfirst)
File "/Users/marti/anaconda3/envs/PROD/lib/python3.7/site-packages/matplotlib/legend.py", line 767, in _init_legend_box
fontsize, handlebox))
File "/Users/marti/anaconda3/envs/PROD/lib/python3.7/site-packages/matplotlib/legend_handler.py", line 117, in legend_artist
fontsize, handlebox.get_transform())
File "/Users/marti/anaconda3/envs/PROD/lib/python3.7/site-packages/matplotlib /legend_handler.py", line 727, in create_artists
self.update_prop(p, orig_handle, legend)
File "/Users/marti/anaconda3/envs/PROD/lib/python3.7/site-packages/matplotlib/legend_handler.py", line 76, in update_prop
legend._set_artist_props(legend_handle)
File "/Users/marti/anaconda3/envs/PROD/lib/python3.7/site-packages/matplotlib/legend.py", line 550, in _set_artist_props
a.set_figure(self.figure)
File "/Users/marti/anaconda3/envs/PROD/lib/python3.7/site-packages/matplotlib/artist.py", line 704, in set_figure
raise RuntimeError("Can not put single artist in "
RuntimeError: Can not put single artist in more than one figure
Any hint to fix this?
The artist object involved has deep nested data that matplotlib chooses not to allow its reuse on other axes. The workaround code can be something like this: (only relevant code towards the end is given here) # if want to plot the filled patch, must create anew grey_patch1 = mpatches.Patch(label='filling1', alpha=0.2, color='grey') plt.legend(handles=[line1, line2, grey_patch1]) plt.show() #grey_patch1 can be reused, no need to recreate like this grey_patch2 = mpatches.Patch(label='filling2', alpha=0.2, color='red') plt.legend(handles=[grey_patch1, grey_patch2,]) plt.show() The above code needs import matplotlib.patches as mpatches.
Stop x-axis labels from shrinking the plot in Matplotlib?
I'm trying to make a bar graph with the following code:
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
test = {'names':['a','b','abcdefghijklmnopqrstuvwxyz123456789012345678901234567890'], 'values':[1,2,3]}
df = pd.DataFrame(test)
plt.rcParams['figure.autolayout'] = False
ax = sns.barplot(x='names', y='values', data=df)
ax.set_xticklabels(ax.get_xticklabels(), rotation=90)
plt.show()
But I get the following error because the long value in 'names' as a label on the x-axis is making the image shrink until the bottom is above the top.
Traceback (most recent call last):
File "C:/Users/Adam/.PyCharm2018.2/config/scratches/scratch.py", line 11, in <module>
plt.show()
File "C:\Anaconda3\lib\site-packages\matplotlib\pyplot.py", line 253, in show
return _show(*args, **kw)
File "C:\Program Files\JetBrains\PyCharm 2018.2.3\helpers\pycharm_matplotlib_backend\backend_interagg.py", line 25, in __call__
manager.show(**kwargs)
File "C:\Program Files\JetBrains\PyCharm 2018.2.3\helpers\pycharm_matplotlib_backend\backend_interagg.py", line 107, in show
self.canvas.show()
File "C:\Program Files\JetBrains\PyCharm 2018.2.3\helpers\pycharm_matplotlib_backend\backend_interagg.py", line 62, in show
self.figure.tight_layout()
File "C:\Anaconda3\lib\site-packages\matplotlib\figure.py", line 2276, in tight_layout
self.subplots_adjust(**kwargs)
File "C:\Anaconda3\lib\site-packages\matplotlib\figure.py", line 2088, in subplots_adjust
self.subplotpars.update(*args, **kwargs)
File "C:\Anaconda3\lib\site-packages\matplotlib\figure.py", line 245, in update
raise ValueError('bottom cannot be >= top')
ValueError: bottom cannot be >= top
Here is what it looks like if I reduce the length of that name slightly:
How can I get it to expand the figure to fit the label instead of shrinking the axes?
One workaround is to create the Axes instance yourself as axes, not as subplot. Then tight_layout() has no effect, even if it's called internally. You can then pass the Axes with the ax keyword to sns.barplot. The problem now is that if you call plt.show() the label may be cut off, but if you call savefig with bbox_inches='tight', the figure size will be extended to contain both the figure and all labels:
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
fig = plt.figure()
ax = fig.add_axes([0,0,1,1])
test = {'names':['a','b','abcdefghijklmnopqrstuvwxyz123456789012345678901234567890'], 'values':[1,2,3]}
df = pd.DataFrame(test)
#plt.rcParams['figure.autolayout'] = False
ax = sns.barplot(x='names', y='values', data=df, ax=ax)
ax.set_xticklabels(ax.get_xticklabels(), rotation=90)
#plt.show()
fig.savefig('long_label.png', bbox_inches='tight')
PROCLAIMER: I don't have pycharm, so there goes the assumption in this code, that matplotlib behaves the same with and without pycharm. Anyway, for me the outcome looks like this:
If you want this in an interactive backend I didn't find any other way than manually adjust the figure size. This is what I get using the qt5agg backend: ax = sns.barplot(x='names', y='values', data=df) ax.set_xticklabels(ax.get_xticklabels(), rotation=90) ax.figure.set_size_inches(5, 8) # manually adjust figure size plt.tight_layout() # automatically adjust elements inside the figure plt.show() Note that pycharm's scientific mode might be doing some magic that prevents this to work so you might need to deactivate it or just run the script outside pycharm.
How to connect points to draw a line segment and also make a parallel line w.r.t. line segment?
I want to draw a line segment passing through all the end points of my graph (the maximum value of a curve) which is plotted from a csv file. For this line segment I also need to draw a line parallel to this line segments by taking one point(known) as reference on the curve.
z, x, y
-40,0,0
-40,0.658,26.443
-40,1.316,47.128
-40,1.974,62.084
-40,2.632,73.336
-40,3.29,81.785
-40,3.948,87.501
-40,4.606,90.795
-40,5.264,92.491
-40,5.922,93.231
-40,6.58,93.41 - maximum value i.e end point of the curve
23,0,0
23,0.889,22.616
23,1.778,36.552
23,2.667,45.238
23,3.556,50.666
23,4.445,53.856
23,5.334,55.673
23,6.223,56.672
23,7.112,57.203
23,8.001,57.443
23,8.89,57.51- maximum value i.e end point of the curve
40,0,0
40,0.937,19.191
40,1.874,30.893
40,2.811,38.58
40,3.748,43.547
40,4.685,46.518
40,5.622,48.238
40,6.559,49.193
40,7.496,49.694
40,8.433,49.935
40,9.37,50.02- maximum value i.e end point of the curve
Above is the CSV file which I need to plot and the end points are mentioined. I need to connect all the end points with a line as in the image by using Pandas function and I tried the below code for doing this. The parallel line for instance take a single point on any curve w.r.t. this point the line to be drawn and should be parallel to the first line.
import csv
from tkinter import filedialog
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
from matplotlib import style
from mpldatacursor import datacursor
x=[] # Initializing empty lists to store the 3 columns in csv
y=[]
z=[]
df = pd.DataFrame({'A' : []})
def readCSV(e):
global df
filename = filedialog.askopenfilename()
df = pd.read_csv(filename, error_bad_lines=False) #Reading CSV file using pandas
read = csv.reader(df, delimiter = ",")
fig = plt.figure()
data_list = []
ax= fig.add_subplot(111)
df.set_index('x', inplace=True) #Setting index
df.groupby('z')['y'].plot(legend=True,ax=ax) #grouping and plotting
for line in ax.lines:
xdata = line.get_xdata()
ydata = line.get_ydata()
s = line.append([6.58,8.89,9.37])
r = line.append([93.41,57.51,50.02])
ax.plot(s,r)
ax.set_ylabel('y')
ax.set_xlabel('x')
ax.grid(True)
plt.show()
To plot a line connecting the end points of your graph, one way would be to get the last set of coordinates for each line. This can be done using get_xdata() and get_ydata(). This returns all the values, but we only want the last value. This can be done using the slice notation [-1]:
my_list = [1,2,3,4,5]
print (my_list[-1])
# 5
So your code would become something like:
s = []
r = []
df = pd.read_csv("test.csv", error_bad_lines=False) #Reading CSV file using pandas
fig = plt.figure()
data_list = []
ax= fig.add_subplot(111)
df.set_index('x', inplace=True) #Setting index
df.groupby('z')['y'].plot(legend=True,ax=ax) #grouping and plotting
for line in ax.lines:
s.append(line.get_xdata()[-1])
r.append(line.get_ydata()[-1])
ax.plot(s, r, color="black", linestyle=":")
ax.set_ylabel('y')
ax.set_xlabel('x')
ax.grid(True)
plt.show()
Which gives: