{"id":20178002,"url":"https://github.com/sefakcmn00/python-for-finance-cryptocurrency-analysis","last_synced_at":"2026-04-28T17:04:24.645Z","repository":{"id":122466022,"uuid":"522031268","full_name":"sefakcmn00/Python-For-Finance-Cryptocurrency-Analysis","owner":"sefakcmn00","description":"In this project, after extracting the data sets as csv, we tried to reflect them graphically and schematically about cryptocurrencies in finance by using data analysis and data visualization methods. In this project, there are other cryptocurrencies in the data set we provided in this project, but if you want, you can do the same after reading them as csv files. We used 3 cryptocurrencies of our choice. 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In this project, there are other cryptocurrencies in the data set we provided in this project, but if you want, you can do the same after reading them as csv files. We used 3 cryptocurrencies of our choice. These are Ethereum, bitcoin and dogecoin.\n## Libraries and Utilities\n\n```Python\nimport numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\n```\n### Let's take a look at our top five data\n\n```Python\ndf_btc.head()\n```\n\n![1](https://user-images.githubusercontent.com/77057546/183245584-4415aad9-90fa-469b-a8c8-21983f3208e2.png)\n\n```Python\ndf = pd.DataFrame({'BTC': df_btc['Close'],\n'ETH': df_eth['Close'],\n'DOGE': df_doge['Close']})\ndf.head()\n```\n![2](https://user-images.githubusercontent.com/77057546/183245627-d0f3cc95-1e89-494c-a0eb-5d018f1939c2.png)\n\n### Cryptocurrency Graph\n\n```Python\nimport matplotlib.pyplot as plt\nplt.style.use('fivethirtyeight')\nmy_crypto = df\nplt.figure(figsize = (12.2, 4.5))\nfor c in my_crypto.columns.values:\n   plt.plot(my_crypto[c], label = c)\nplt.title('Cryptocurrency Graph')\nplt.xlabel('Days')\nplt.ylabel(' Crypto Price ($)')\nplt.legend(my_crypto.columns.values, loc= 'upper left')\nplt.show()\n```\n\n![3](https://user-images.githubusercontent.com/77057546/183245736-39aae06f-170e-4565-9cf8-61c6bed6bd57.png)\n\n### Cryptocurrency Scaled Graph\n\n```Python\n#Visualize the scaled data\nmy_crypto = df_scale\nplt.figure(figsize=(12.4, 4.5))\nfor c in my_crypto.columns.values:\n   plt.plot(my_crypto[c], label=c)\nplt.title('Cryptocurrency Scaled Graph')\nplt.xlabel('Days')\nplt.ylabel('Crypto Scaled Price ($)')\nplt.legend(my_crypto.columns.values, loc = 'upper left')\nplt.show()\n```\n![4](https://user-images.githubusercontent.com/77057546/183245806-8630c99a-ccc7-4f7a-b030-bd5549c1e457.png)\n\n### Daily Simple Returns\n\n```Python\nplt.figure(figsize=(12, 4.5))\nfor c in DSR.columns.values:\n   plt.plot(DSR.index, DSR[c], label = c, lw = 2, alpha = .7)\nplt.title('Daily Simple Returns')\nplt.ylabel('Percentage (in decimal form')\nplt.xlabel('Days')\nplt.legend(DSR.columns.values, loc= 'upper right')\nplt.show()\n```\n![5](https://user-images.githubusercontent.com/77057546/183245879-63dacefe-20cc-4090-b32e-51f8bd854772.png)\n\n### Heat Map\n\n```Python\nimport seaborn as sns\nplt.subplots(figsize= (11,11))\nsns.heatmap(DSR.corr(), annot= True, fmt= '.2%')\n```\n\n![6](https://user-images.githubusercontent.com/77057546/183245943-3e82bad3-1d8a-4b5f-8b8c-9c9b9b376c54.png)\n\n### Daily Cumulative Simple Return\n\n```Python\nplt.figure(figsize=(12.2, 4.5))\nfor c in DCSR.columns.values:\n  plt.plot(DCSR.index, DCSR[c], lw=2, label= c)\nplt.title('Daily Cumulative Simple Return')\nplt.xlabel('Days')\nplt.ylabel('Growth of $1 investment')\nplt.legend(DCSR.columns.values, loc = 'upper left', fontsize = 10)\nplt.show()\n```\n![7](https://user-images.githubusercontent.com/77057546/183245991-53b463e7-1509-4524-ab88-32868ec94863.png)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsefakcmn00%2Fpython-for-finance-cryptocurrency-analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsefakcmn00%2Fpython-for-finance-cryptocurrency-analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsefakcmn00%2Fpython-for-finance-cryptocurrency-analysis/lists"}