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For the following dataframe, I am trying to plot the means of a sample of 5 random rows . And also plot their respective confidence intervals using errorbars. I am unable to figure how to plot the confidence intervals using errorbars.

  col0  col1  col2  col3  col4  col5  col6  col7
0     0     1     2     3     4     5     6     7
1     8     9    10    11    12    13    14    15
2    16    17    18    19    20    21    22    23
3    24    25    26    27    28    29    30    31
4    32    33    34    35    36    37    38    39
5    40    41    42    43    44    45    46    47
6    48    49    50    51    52    53    54    55
7    56    57    58    59    60    61    62    63

Here is my code:

confidenceInterval_percent = 0.95
sample_size=5
mean_list=[]
df = pd.DataFrame(np.arange(64).reshape(8,8)).add_prefix('col')
sample_df= df.sample(n=sample_size, random_state=10)
for i in df.columns:
    mean = df[i].mean()
    mean_list.append(mean)
    stdError = df[i].std() / np.sqrt(sample_size)
    confidence_intervals = sp.stats.norm.interval(
                        confidenceInterval_percent, loc = mean, 
                           scale = stdError)
    temporary_Df=pd.DataFrame(mean_list)
    temporary_Df.plot.bar()
    plt.show()
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1 Answer 1

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For a confidence level of 95%, you can calculate the mean and sample standard deviation, then find the bands of your interval with: $\bar{x} \pm 1.96*\frac{s}{\sqrt{n}}$

By creating an array with each pair of values for each sample, you can then plot them on your chart.

Matplotlib has a great method for adding error bars, check it out: https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.errorbar.html

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