<jupyter_start><jupyter_text>**Importing Libraries**<jupyter_code>import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt<jupyter_output>/usr/local/lib/python3.6/dist-packages/statsmodels/tools/_testing.py:19: FutureWarning: pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead.
  import pandas.util.testing as tm<jupyter_text>**Importing Covid -19 Deaths Dataset**<jupyter_code>from google.colab import files
uploaded = files.upload()
data_set = pd.read_csv("covid19_deaths_dataset.csv")
data_set.head()<jupyter_output><empty_output><jupyter_text>**Check the shape of the data frame**<jupyter_code>data_set.shape<jupyter_output><empty_output><jupyter_text>**Delete the unwanted Coloumns**<jupyter_code>data_set.drop(["Lat","Long"],axis = 1,inplace = True)
data_set.head()<jupyter_output><empty_output><jupyter_text>**Aggregating the rows by the country**<jupyter_code>data_set_aggregated = data_set.groupby("Country/Region").sum()
data_set_aggregated.head()
data_set_aggregated.shape<jupyter_output><empty_output><jupyter_text>**Visualizing the data related to a specific country**<jupyter_code>data_set_aggregated.loc['India'].plot()
data_set_aggregated.loc["China"].plot()
data_set_aggregated.loc["Italy"].plot()
plt.legend()<jupyter_output><empty_output><jupyter_text>**Calculating a good measure**<jupyter_code>data_set_aggregated.loc["India"][:6].plot()<jupyter_output><empty_output><jupyter_text>**Calculating and plotting the first derivative of the curve**<jupyter_code>data_set_aggregated.loc["India"].diff().plot()<jupyter_output><empty_output><jupyter_text>**Calculating the maximum fatality rate for India,China,Italy**<jupyter_code>data_set_aggregated.loc["India"].diff().max()
data_set_aggregated.loc["Italy"].diff().max()
data_set_aggregated.loc["China"].diff().max()<jupyter_output><empty_output><jupyter_text>**Caculating the max fatality rate for all the countries**<jupyter_code>countries= list(data_set_aggregated.index)
max_fatality_rate = []
for c in countries:
   max_fatality_rate.append(data_set_aggregated.loc[c].diff().max())
data_set_aggregated["max fatality rate"] = max_fatality_rate
data_set_aggregated.head()<jupyter_output><empty_output><jupyter_text>**Create a new dataframe for max fatality rate**<jupyter_code>corona_fatality_rate = pd.DataFrame(data_set_aggregated["max fatality rate"])
corona_fatality_rate.head()<jupyter_output><empty_output>
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