How to plot a histogram using Matplotlib in Python with a list of data

Question

I am trying to plot a histogram using the matplotlib hist   function but I am not sure how to do it   I have a list   probability    0 3602150537634409  0 42028985507246375     0 373117033603708  0 36813186813186816  0 32517482517482516     0 4175257731958763  0 41025641025641024  0 39408866995073893     0 4143222506393862  0 34  0 391025641025641  0 3130841121495327     0 35398230088495575    and a list of names strings    How do I make the probability as my y-value of each bar and names as x-values

User · Answer

This is a very round-about way of doing it but if you want to make a histogram where you already know the bin values but dont have the source data, you can use the np.random.randint function to generate the correct number of values within the range of each bin for the hist function to graph, for example:

import numpy as np
import matplotlib.pyplot as plt

data = [np.random.randint(0, 9, *desired y value*), np.random.randint(10, 19, *desired y value*), etc..]
plt.hist(data, histtype='stepfilled', bins=[0, 10, etc..])

as for labels you can align x ticks with bins to get something like this:

#The following will align labels to the center of each bar with bin intervals of 10
plt.xticks([5, 15, etc.. ], ['Label 1', 'Label 2', etc.. ])

User · Answer

Though the question appears to be demanding plotting a histogram using matplotlib hist   function  it can arguably be not done using the same as the latter part of the question demands to use the given probabilities as the y-values of bars and given names strings  as the x-values   I m assuming a sample list of names corresponding to given probabilities to draw the plot  A simple bar plot serves the purpose here for the given problem  The following code can be used   import matplotlib pyplot as plt probability    0 3602150537634409  0 42028985507246375     0 373117033603708  0 36813186813186816  0 32517482517482516     0 4175257731958763  0 41025641025641024  0 39408866995073893     0 4143222506393862  0 34  0 391025641025641  0 3130841121495327     0 35398230088495575  names     name1    name2    name3    name4    name5    name6    name7    name8    name9    name10    name11    name12    name13    sample names plt bar names  probability  plt xticks names  plt yticks probability   This may be included or excluded as per need plt xlabel  Names   plt ylabel  Probability

User · Answer

If you want a histogram  you don t need to attach any  names  to x-values  as on x-axis you would have data bins  import matplotlib pyplot as plt import numpy as np  matplotlib inline  np random seed 42  x   np random normal size 1000   plt hist x  density True  bins 30     density False would make counts plt ylabel  Probability   plt xlabel  Data      Note  the number of bins 30 was chosen arbitrarily  and there is Freedman   Diaconis rule to be more scientific in choosing the  quot right quot  bin width      where IQR is Interquartile range and n is total number of datapoints to plot  So  according to this rule one may calculate number of bins as  q25  q75   np percentile x   25  75   bin width   2  q75 - q25  len x    -1 3  bins   round  x max   - x min    bin width  print  quot Freedman   Diaconis number of bins  quot   bins  plt hist x  bins   bins     Freedman   Diaconis number of bins  82   And finally you can make your histogram a bit fancier with PDF line  titles  and legend  import scipy stats as st  plt hist x  density True  bins 82  label  quot Data quot   mn  mx   plt xlim   plt xlim mn  mx  kde xs   np linspace mn  mx  300  kde   st gaussian kde x  plt plot kde xs  kde pdf kde xs   label  quot PDF quot   plt legend loc  quot upper left quot   plt ylabel  Probability   plt xlabel  Data   plt title  quot Histogram quot      However  if you have limited number of data points  like in OP  a bar plot would make more sense to represent your data  Then you may attach labels to x-axis  x   np arange 3  plt bar x  height  1 2 3   plt xticks x    a   b   c

User · Answer

If you haven t installed matplotlib yet just try the command    gt  pip install matplotlib   Library import  import matplotlib pyplot as plot   The histogram data   plot hist weightList density 1  bins 20   plot axis  50  110  0  0 06     axis  xmin xmax ymin ymax   plot xlabel  Weight   plot ylabel  Probability     Display histogram  plot show     And the output is like

User · Answer

This is an old question but none of the previous answers has addressed the real issue  i e  that fact that the problem is with the question itself  First  if the probabilities have been already calculated  i e  the histogram aggregated data is available in a normalized way then the probabilities should add up to 1  They obviously do not and that means that something is wrong here  either with terminology or with the data or in the way the question is asked  Second  the fact that the labels are provided  and not intervals  would normally mean that the probabilities are of categorical response variable - and a use of a bar plot for plotting the histogram is best  or some hacking of the pyplot s hist method   Shayan Shafiq s answer provides the code  However  see issue 1  those probabilities are not correct and using bar plot in this case as  quot histogram quot  would be wrong because it does not tell the story of univariate distribution  for some reason  perhaps the classes are overlapping and observations are counted multiple times   and such plot should not be called a histogram in this case  Histogram is by definition a graphical representation of the distribution of univariate variable  see Histogram   NIST SEMATECH e-Handbook of Statistical Methods  amp  Histogram   Wikipedia  and is created by drawing bars of sizes representing counts or frequencies of observations in selected classes of the variable of interest  If the variable is measured on a continuous scale those classes are bins  intervals   Important part of histogram creation procedure is making a choice of how to group  or keep without grouping  the categories of responses for a categorical variable  or how to split the domain of possible values into intervals  where to put the bin boundaries  for continuous type variable  All observations should be represented  and each one only once in the plot  That means that the sum of the bar sizes should be equal to the total count of observation  or their areas in case of the variable widths  which is a less common approach   Or  if the histogram is normalised then all probabilities must add up to 1  If the data itself is a list of  quot probabilities quot  as a response  i e  the observations are probability values  of something  for each object of study then the best answer is simply plt hist probability  with maybe binning option  and use of x-labels already available is suspicious  Then bar plot should not be used as histogram but rather simply import matplotlib pyplot as plt probability    0 3602150537634409  0 42028985507246375     0 373117033603708  0 36813186813186816  0 32517482517482516     0 4175257731958763  0 41025641025641024  0 39408866995073893     0 4143222506393862  0 34  0 391025641025641  0 3130841121495327     0 35398230088495575  plt hist probability  plt show    with the results  matplotlib in such case arrives by default with the following histogram values  array  1   1   1   1   1   2   0   2   0   4      array  0 31308411  0 32380469  0 33452526  0 34524584  0 35596641          0 36668698  0 37740756  0 38812813  0 39884871  0 40956928          0 42028986      lt a list of 10 Patch objects gt    the result is a tuple of arrays  the first array contains observation counts  i e  what will be shown against the y-axis of the plot  they add up to 13  total number of observations  and the second array are the interval boundaries for x-axis  One can check they they are equally spaced  x   plt hist probability  1  for left  right in zip x  -1   x 1       print left  right  right-left    Or  for example for 3 bins  my judgment call for 13 observations  one would get this histogram plt hist probability  bins 3    with the plot data  quot behind the bars quot  being  The author of the question needs to clarify what is the meaning of the  quot probability quot  list of values - is the  quot probability quot  just a name of the response variable  then why are there x-labels ready for the histogram  it makes no sense   or are the list values the probabilities calculated from the data  then the fact they do not add up to 1 makes no sense

[python] How to plot a histogram using Matplotlib in Python with a list of data?

Examples related to python

Examples related to matplotlib

Examples related to visualization

Examples related to data-visualization