Tell us what’s happening:
Hi, when i run the project i get the following error:
ERROR: test_data_cleaning (test_module.DataCleaningTestCase)
Traceback (most recent call last):
File “/home/runner/boilerplate-page-view-time-series-visualizer/test_module.py”, line 7, in test_data_cleaning
actual = int(time_series_visualizer.df.count(numeric_only=True))
File “/home/runner/boilerplate-page-view-time-series-visualizer/.pythonlibs/lib/python3.10/site-packages/pandas/core/series.py”, line 230, in wrapper
raise TypeError(f"cannot convert the series to {converter}")
TypeError: cannot convert the series to <class ‘int’>
Ran 11 tests in 4.031s
FAILED (errors=1)
I think the project works fine, i get the plots like the example but i don’t understand why i have the error.
When i run the code in a ipynb it works fine without any error message.
I also have tried to re import the project as a new, copy code from the first one and paste in the new imported project but i have the same error.
Your code so far
import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
from pandas.plotting import register_matplotlib_converters
register_matplotlib_converters()
# Import data (Make sure to parse dates. Consider setting index column to 'date'.)
df = pd.read_csv("fcc-forum-pageviews.csv", parse_dates=["date"]).set_index("date")
# Clean data
top_threshold = df['value'].quantile(0.975)
bottom_threshold = df['value'].quantile(0.025)
df = df[(df['value'] <= top_threshold) & (df['value'] >= bottom_threshold)]
def draw_line_plot():
# Draw line plot
fig, ax = plt.subplots()
plot = ax.plot(df["value"])
# Customize the plot (optional)
ax.set_xlabel("Date")
ax.set_ylabel("Page Views")
ax.set_title("Daily freeCodeCamp Forum Page Views 5/2016-12/2019")
# Save image and return fig (don't change this part)
fig.savefig('line_plot.png')
return fig
def draw_bar_plot():
# Copy and modify data for monthly bar plot
df_bar = df
# Extract year and month from the 'date' column
df_bar['year'] = df.index.year
df_bar['month'] = df.index.month
# Create a pivot table to calculate average page views per month
pivot_table = df.pivot_table(index='year', columns='month', values='value', aggfunc='mean')
month_labels = ['January', 'February', 'March', 'April', 'May', 'June',
'July', 'August', 'September', 'October', 'November', 'December']
# Draw bar plot
fig, ax = plt.subplots(figsize=(12, 6))
pivot_table.plot(kind='bar', ax=ax)
ax.set_xlabel('Years')
ax.set_ylabel('Average Page Views')
ax.set_title('Average Daily Page Views per Month (2016-2019)')
ax.set_xticklabels(df['year'].unique(), rotation=0)
ax.set_xticks(range(len(df['year'].unique())))
ax.legend(title='Months', labels=month_labels)
# Save image and return fig (don't change this part)
fig.savefig('bar_plot.png')
return fig
def draw_box_plot():
# Prepare data for box plots (this part is done!)
df_box = df.copy()
df_box.reset_index(inplace=True)
df_box['year'] = [d.year for d in df_box.date]
df_box['month'] = [d.strftime('%b') for d in df_box.date]
# Draw box plots (using Seaborn)
df_box["month_num"]=df_box["date"].dt.month
df_box=df_box.sort_values("month_num")
fig, axes = plt.subplots(1, 2, figsize=(15, 6))
# Plot Year-wise Box Plot
sns.boxplot(x='year', y='value', data=df_box, ax=axes[0])
axes[0].set_xlabel('Year')
axes[0].set_ylabel('Page Views')
axes[0].set_title('Year-wise Box Plot (Trend)')
# Plot Month-wise Box Plot
sns.boxplot(x='month', y='value', data=df_box, ax=axes[1], order=[
'Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun',
'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec'
])
axes[1].set_xlabel('Month')
axes[1].set_ylabel('Page Views')
axes[1].set_title('Month-wise Box Plot (Seasonality)')
# Save image and return fig (don't change this part)
fig.savefig('box_plot.png')
return fig
Could you please help me with this?
link to replit:
https://replit.com/@info359/boilerplate-page-view-time-series-visualizer#time_series_visualizer.py
Thanks a lot
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Challenge: Data Analysis with Python Projects - Page View Time Series Visualizer
Link to the challenge: