spotify.ipynb

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   "source": [
    "## 1. Importing Libraries"
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   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
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   "source": [
    "## 2. Loading Spotify dataset"
   ]
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   "source": [
    "----------"
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   "source": [
    "## 1. Are there any missing values in the dataset?"
   ]
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   "source": [
    "## 2. How many songs are there in the dataset?"
   ]
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    "## 3. What's the average duration of a song, in minutes?"
   ]
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   "source": [
    "## 4. Can you plot the distribution of the durations?"
   ]
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   "source": [
    "## 5. [Follow-up] Can you make this plot more readable by removing outliers (extreme values)?"
   ]
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   "source": [
    "We get a way more interesting plot!"
   ]
  },
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   "source": [
    "## 6. How long would it take to listen to all the songs?"
   ]
  },
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  {
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   "source": [
    "This length is expressed in milliseconds, let's convert to days!"
   ]
  },
  {
   "cell_type": "markdown",
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   "source": [
    "## 7. What are the top 10 most popular songs? We would like a DataFrame with only the columns `artists`, `name` and `popularity` as output!"
   ]
  },
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   "source": [
    "## 8. Can you plot the distribution of `popularity`?"
   ]
  },
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   "source": [
    "## 9. What are the top 10 artists in terms of number of songs?"
   ]
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   "source": [
    "## 10. [Follow-up] can you make a bar chart out of this result?"
   ]
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   "source": [
    "## 11. Can you plot a line graph representing the annual number of songs since 1921?"
   ]
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   "source": [
    "Why do we get this weird plot? Try sorting the indexes :)"
   ]
  },
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   "source": [
    "## 12. Can you visually check if there is relationship between `year` and `popularity`?"
   ]
  },
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   "source": [
    "It seems that the popularity score has increased through time...."
   ]
  },
  {
   "cell_type": "markdown",
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   "source": [
    "## 12. Can you show a dataframe showing the mean of danceability, instrumentalness and energy for every year ? "
   ]
  },
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