Python combo chart add the percentage on the bar but wrong

Question

I tried to add the percentage on the bar in combo chart, line and column graphs.
However, all the values displayed are messy.

I provide the data here, this is also my previous post and the answer is provided by Quang Hoang.

Group   yq        Value1    Value2
G       2014Q1     0.07        1.1
G       2014Q2     0.06        1.09
G       2014Q3     0.09        1.11
G       2014Q4     0.04        1.13
I       2014Q1     0.10        1.2
I       2014Q2     0.13        1.25
I       2014Q3     0.15        1.23
I       2014Q4     0.18        1.4

I provided the code I tried:

fig, ax1 = plt.subplots(figsize=(7,5))
ax2=ax1.twinx()
sns.lineplot(x='yq',y='Value2', data=dataset, hue='Group', ax=ax1, legend = None)
ax1.set_xticklabels(ax1.get_xticks(), rotation=45)
ax1.set_ylabel("")
ax1.set_ylim((min(dataset['Value2']) - 0.05, max(dataset['Value2']) + 0.05))
sns.barplot(x='yq', y='Value1', data=dataset, hue='Group',ax=ax2)
ax2.set_yticklabels(['{:.1f}%'.format(a*100) for a in ax2.get_yticks()])
ax2.set_ylabel("")
for index, row in dataset.iterrows():
    ax2.text(row.name,row['Value1'], '{:.1f}%'.format(round(row['Value1'],2)), color='black')
plt.show()

The percentages showing on the plot are messy and do not place properly on each bar and group.
I searched on here and here but I cannot solve it.
Any solution?

I provide my result:

I also provide the correct resulting image created by R's package ggplot2.
There are two packages similar to ggplot2 in Python, plotnine and ggplot. However, I cannot use it in my Python.

I provide my R code as your reference if it helps:

library(data.table)
library(ggplot2)
library(zoo)
dataset <- fread("Group   yq        Value1    Value2
G       2014/1/1     0.07        1.1
G       2014/4/1     0.06        1.09
G       2014/7/1     0.09        1.11
G       2014/10/1     0.04        1.13
I       2014/1/1     0.10        1.2
I       2014/4/1     0.13        1.25
I       2014/7/1     0.15        1.23
I       2014/10/1     0.18        1.4", header = T)
dataset$yq <- as.Date(dataset$yq)
dataset[, yq := as.yearqtr(dataset$yq, format = "%Y-%m-%d")]

ggplot(data = dataset, aes(x = yq, colour = Group, fill = Group,
                           label = scales::percent(Value1, accuracy = 0.1))) + 
  geom_col(aes(y = sec_axis_mult * Value1), position = position_dodge2(width = 0)) +
  geom_line(aes(y = Value2)) +
  scale_colour_manual(values = c("red", "darkblue"), labels = c("G", "I")) +
  scale_fill_manual(values = c("red", "darkblue"), labels = NULL, breaks = NULL) +
  scale_x_yearqtr(format = "%YQ%q", breaks = unique(dataset$yq)) +
  scale_y_continuous(name = "Value2",
                     sec.axis = sec_axis(~./sec_axis_mult, name = "Value1",
                                         labels = scales::percent)) +
  theme_bw() +
  theme(axis.title.x = element_blank(),
        axis.title.y = element_blank(),
        axis.title.y.right = element_blank(),
        axis.ticks.x=element_blank(),
        axis.ticks.y=element_blank(),
        axis.text.x=element_text(angle = 45, size = 12, vjust = 0.5, face = "bold"),
        axis.text.y=element_blank(),
        axis.line = element_line(colour = "white"),
        panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(),
        panel.border = element_blank(),
        panel.background = element_blank(),
        plot.background=element_blank(),
        legend.position="left",
        legend.title=element_blank(),
        legend.text = element_text(size = 16, face = "bold"),
        legend.key = element_blank(),
        legend.box.background =  element_blank()) +
  guides(colour = guide_legend(override.aes = list(shape = 15, size = 10))) +
  geom_text(data = dataset, aes(y = sec_axis_mult * Value1, colour = Group), 
            position = position_dodge(width = 0.25),
            vjust = -0.3, size = 4)

Answer 1

What I'm doing is dynamically labeling the bar graphs based on the coordinates for each patch that's drawn by the bar function.

fig, ax1 = plt.subplots(figsize=(7,5))
ax2=ax1.twinx()
sns.lineplot(x='yq',y='Value2', data=dataset, hue='Group', ax=ax1, legend = None)
ax1.set_xticklabels(ax1.get_xticks(), rotation=45)
ax1.set_ylabel("")
ax1.set_ylim((min(dataset['Value2']) - 0.05, max(dataset['Value2']) + 0.05))
sns.barplot(x='yq', y='Value1', data=dataset, hue='Group',ax=ax2)
ax2.set_yticklabels(['{:.1f}%'.format(a*100) for a in ax2.get_yticks()])
ax2.set_ylabel("")
#iterate through each group of bars
for group in ax2.containers:
    for bar in group:
        #label the bar graphs based on the coordinates of the bar patches
        ax2.text(
            bar.get_xy()[0]+bar.get_width()/2,
            bar.get_height(), 
            '{:.1f}%'.format(round(100*bar.get_height(),2)), 
            color='black',
            horizontalalignment='center'
        )

Output:

I've adjusted the code to more closely match the desired output that's been added to the original question.

fig, ax1 = plt.subplots(figsize=(7,5))
ax2=ax1.twiny().twinx()
sns.lineplot(x='yq',y='Value2', data=dataset, hue='Group', ax=ax1, legend = None)
ax1.set_xticklabels(dataset['yq'], rotation=45)
ax1.set_ylabel("")
ax1.set_ylim((0, max(dataset['Value2']) + 0.05))
ax2.set_ylim(0, max(dataset['Value2']) + 0.05)
sns.barplot(x='yq', y='Value1', data=dataset, hue='Group',ax=ax2)

#iterate through each group of bars
for group in ax2.containers:
    for bar in group:
        #label the bar graphs based on the coordinates of the bar patches
        ax2.text(
            bar.get_xy()[0]+bar.get_width()/2,
            bar.get_height(), 
            '{:.1f}%'.format(100*bar.get_height()), 
            color='black',
            horizontalalignment='center'
        )

ax1.yaxis.set_visible(False)
ax2.yaxis.set_visible(False)
ax2.xaxis.set_visible(False)

Outputs: