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Seaborn barplot wrong order when using numbers in factor even its type is string


Seaborn barplot wrong order when using numbers in factor even its type is string

By : Drew Einhorn
Date : November 20 2020, 03:01 PM
will be helpful for those in need d contains strings. As such, they are sorted as words ("6" is higher up than "10" since the letter "6" is higher than "1").
Change it to integers to have the order you expect in general.
code :
sns.barplot(d, value,order=d)


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how to change the order of factor plot in seaborn

how to change the order of factor plot in seaborn


By : user2055256
Date : March 29 2020, 07:55 AM
this will help Your update to the post shows the correct way to do it, i.e. you should pass a list of x values to order in the order you want them plotted. The default for numeric data is to plot in sorted order, so if you have numeric values it's best to keep them as integers or floats instead of strings, so they will be in "natural" order.
How to change order barplot seaborn

How to change order barplot seaborn


By : Keerthi Suria Kumar
Date : March 29 2020, 07:55 AM
Hope that helps I have data as bellow , Reverse both lists in-place before plotting them:
code :
df["Shkala"].reverse()
df["Ves"].reverse()
order = list(reversed(df["Shkala"]))
Ascending order of bars in seaborn barplot

Ascending order of bars in seaborn barplot


By : Mohan
Date : March 29 2020, 07:55 AM
will help you The seaborn hue parameter adds another dimension to the plot. The hue_order determines in which order this dimension is handled. However you cannot split that order. This means you may well change the order such that Age == 2 is in the third place in the plot. But you cannot change it partially, such that in some part it is in the first and in some other it'll be in the third place.
In order to achieve what is desired here, namely to use different orders of the auxilary dimensions within the same axes, you need to handle this manually.
code :
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np

df = pd.DataFrame({"Class" : [2004]*6+[2005]*7,
                   "Age" : [3,2,4,6,5,1,2,3,6,4,5,1,9],
                   "Percentage" : [50,40,30,20,10,30,20,35,40,50,45,30,15]})

def sortedgroupedbar(ax, x,y, groupby, data=None, width=0.8, **kwargs):
    order = np.zeros(len(data))
    df = data.copy()
    for xi in np.unique(df[x].values):
        group = data[df[x] == xi]
        a = group[y].values
        b = sorted(np.arange(len(a)),key=lambda x:a[x],reverse=True)
        c = sorted(np.arange(len(a)),key=lambda x:b[x])
        order[data[x] == xi] = c   
    df["order"] = order
    u, df["ind"] = np.unique(df[x].values, return_inverse=True)
    step = width/len(np.unique(df[groupby].values))
    for xi,grp in df.groupby(groupby):
        ax.bar(grp["ind"]-width/2.+grp["order"]*step+step/2.,
               grp[y],width=step, label=xi, **kwargs)
    ax.legend(title=groupby)
    ax.set_xticks(np.arange(len(u)))
    ax.set_xticklabels(u)
    ax.set_xlabel(x)
    ax.set_ylabel(y)


fig, ax = plt.subplots()    
sortedgroupedbar(ax, x="Class",y="Percentage", groupby="Age", data=df)
plt.show()
Conversion from string “” to type Long is not valid...If order number is wrong and i tried only numbers not character

Conversion from string “” to type Long is not valid...If order number is wrong and i tried only numbers not character


By : user1560954
Date : March 29 2020, 07:55 AM
I wish this help you The string "" can not be converted to Long because it is not a number.
You can use TryParse to convert the string to Long. If it can not be parsed then 0 is returned into the variable in the second argument (orderQty):
code :
Dim orderQty As Long
Long.TryParse(txtOrderQty.Text, orderQty)
lblToBeScanned1.Text = (orderQty - lngUPC1).ToString()
How to control the order of bars in a seaborn barplot

How to control the order of bars in a seaborn barplot


By : user2542634
Date : March 29 2020, 07:55 AM
I wish did fix the issue. I have a dataframe with 4000+ observations and two columns of interest: Revenues and cluster_. , Outdated:
code :
sns.barplot(x='cluster_', y='Revenue', data=data7.sort_index())
sorted_keys = ['C', 'B+', 'A+', 'B', 'A'] # for example
sns.barplot(x='cluster_', y='Revenue', data=data7.reindex(sorted_keys))
sns.barplot(x='cluster_', y='Revenue', data=data7, order=['A', 'A+', 'B', 'B+', 'C'])
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